From 5d1875ec4452b5b46f2453bb6ef82c7031af9a64 Mon Sep 17 00:00:00 2001 From: James Hensman Date: Tue, 5 May 2015 14:13:38 +0100 Subject: [PATCH 01/41] preliminary reconfiguring or choleskies ordering --- GPy/core/svgp.py | 2 +- .../latent_function_inference/svgp.py | 39 +- GPy/testing/cython_tests.py | 4 +- GPy/util/choleskies.py | 32 +- GPy/util/choleskies_cython.c | 805 +++++++++--------- GPy/util/choleskies_cython.pyx | 18 +- 6 files changed, 432 insertions(+), 468 deletions(-) diff --git a/GPy/core/svgp.py b/GPy/core/svgp.py index b8df625e..c5eb3374 100644 --- a/GPy/core/svgp.py +++ b/GPy/core/svgp.py @@ -46,7 +46,7 @@ class SVGP(SparseGP): num_latent_functions = Y.shape[1] self.m = Param('q_u_mean', np.zeros((self.num_inducing, num_latent_functions))) - chol = choleskies.triang_to_flat(np.tile(np.eye(self.num_inducing)[:,:,None], (1,1,num_latent_functions))) + chol = choleskies.triang_to_flat(np.tile(np.eye(self.num_inducing)[None,:,:], (num_latent_functions, 1,1))) self.chol = Param('q_u_chol', chol) self.link_parameter(self.chol) self.link_parameter(self.m) diff --git a/GPy/inference/latent_function_inference/svgp.py b/GPy/inference/latent_function_inference/svgp.py index 8d99e750..261a68b6 100644 --- a/GPy/inference/latent_function_inference/svgp.py +++ b/GPy/inference/latent_function_inference/svgp.py @@ -16,11 +16,10 @@ class SVGP(LatentFunctionInference): S = np.empty((num_outputs, num_inducing, num_inducing)) - [np.dot(L[:,:,i], L[:,:,i].T, S[i,:,:]) for i in range(num_outputs)] - S = S.swapaxes(0,2) + [np.dot(L[i,:,:], L[i,:,:].T, S[i,:,:]) for i in range(num_outputs)] #Si,_ = linalg.dpotri(np.asfortranarray(L), lower=1) Si = choleskies.multiple_dpotri(L) - logdetS = np.array([2.*np.sum(np.log(np.abs(np.diag(L[:,:,i])))) for i in range(L.shape[-1])]) + logdetS = np.array([2.*np.sum(np.log(np.abs(np.diag(L[i,:,:])))) for i in range(L.shape[0])]) if np.any(np.isinf(Si)): raise ValueError("Cholesky representation unstable") @@ -46,16 +45,17 @@ class SVGP(LatentFunctionInference): A = np.dot(Knm, Kmmi) mu = prior_mean_f + np.dot(A, q_u_mean - prior_mean_u) #v = Knn_diag[:,None] - np.sum(A*Knm,1)[:,None] + np.sum(A[:,:,None] * np.einsum('ij,jlk->ilk', A, S),1) - v = Knn_diag[:,None] - np.sum(A*Knm,1)[:,None] + np.sum(A[:,:,None] * linalg.ij_jlk_to_ilk(A, S),1) + #v = Knn_diag[:,None] - np.sum(A*Knm,1)[:,None] + np.sum(A[:,:,None] * linalg.ij_jlk_to_ilk(A, S),1) + v = Knn_diag[:,None] - np.sum(A*Knm,1)[:,None] + (S.dot(A.T)*A.T[None,:,:]).sum(1).T #compute the KL term Kmmim = np.dot(Kmmi, q_u_mean) - KLs = -0.5*logdetS -0.5*num_inducing + 0.5*logdetKmm + 0.5*np.sum(Kmmi[:,:,None]*S,0).sum(0) + 0.5*np.sum(q_u_mean*Kmmim,0) + KLs = -0.5*logdetS -0.5*num_inducing + 0.5*logdetKmm + 0.5*np.sum(Kmmi[None,:,:]*S,1).sum(1) + 0.5*np.sum(q_u_mean*Kmmim,0) KL = KLs.sum() #gradient of the KL term (assuming zero mean function) dKL_dm = Kmmim.copy() - dKL_dS = 0.5*(Kmmi[:,:,None] - Si) - dKL_dKmm = 0.5*num_outputs*Kmmi - 0.5*Kmmi.dot(S.sum(-1)).dot(Kmmi) - 0.5*Kmmim.dot(Kmmim.T) + dKL_dS = 0.5*(Kmmi[None,:,:] - Si) + dKL_dKmm = 0.5*num_outputs*Kmmi - 0.5*Kmmi.dot(S.sum(0)).dot(Kmmi) - 0.5*Kmmim.dot(Kmmim.T) if mean_function is not None: #adjust KL term for mean function @@ -80,17 +80,14 @@ class SVGP(LatentFunctionInference): dF_dthetaL = dF_dthetaL.sum(1).sum(1)*batch_scale #derivatives of expected likelihood, assuming zero mean function - Adv = A.T[:,:,None]*dF_dv[None,:,:] # As if dF_Dv is diagonal + Adv = A.T[None,:,:]*dF_dv.T[:,None,:] # As if dF_Dv is diagonal, D, M, N Admu = A.T.dot(dF_dmu) - AdvA = np.dstack([np.dot(A.T, Adv[:,:,i].T) for i in range(num_outputs)]) - #tmp = np.einsum('ijk,jlk->il', AdvA, S).dot(Kmmi) - tmp = linalg.ijk_jlk_to_il(AdvA, S).dot(Kmmi) - dF_dKmm = -Admu.dot(Kmmim.T) + AdvA.sum(-1) - tmp - tmp.T + AdvA = np.dot(Adv, A) # D, M, M + tmp = np.sum([np.dot(a,s) for a, s in zip(AdvA, S)],0).dot(Kmmi) + dF_dKmm = -Admu.dot(Kmmim.T) + AdvA.sum(0) - tmp - tmp.T dF_dKmm = 0.5*(dF_dKmm + dF_dKmm.T) # necessary? GPy bug? - #tmp = 2.*(np.einsum('ij,jlk->ilk', Kmmi,S) - np.eye(num_inducing)[:,:,None]) - tmp = 2.*(linalg.ij_jlk_to_ilk(Kmmi, S) - np.eye(num_inducing)[:,:,None]) - #dF_dKmn = np.einsum('ijk,jlk->il', tmp, Adv) + Kmmim.dot(dF_dmu.T) - dF_dKmn = linalg.ijk_jlk_to_il(tmp, Adv) + Kmmim.dot(dF_dmu.T) + tmp = 2.*(S.dot(Kmmi).swapaxes(1,2) - np.eye(num_inducing)[None, :,:]) # TODO: transpose? + dF_dKmn = np.sum([np.dot(a,b) for a,b in zip(tmp, Adv)],0) + Kmmim.dot(dF_dmu.T) dF_dm = Admu dF_dS = AdvA @@ -103,14 +100,16 @@ class SVGP(LatentFunctionInference): #sum (gradients of) expected likelihood and KL part - log_marginal = F.sum() - KL - dL_dm, dL_dS, dL_dKmm, dL_dKmn = dF_dm - dKL_dm, dF_dS- dKL_dS, dF_dKmm- dKL_dKmm, dF_dKmn + log_marginal = F.sum() + dL_dm, dL_dS, dL_dKmm, dL_dKmn = dF_dm - dKL_dm*0, dF_dS- dKL_dS*0, dF_dKmm- dKL_dKmm*0, dF_dKmn + #log_marginal = F.sum() - KL + #dL_dm, dL_dS, dL_dKmm, dL_dKmn = dF_dm - dKL_dm, dF_dS- dKL_dS, dF_dKmm- dKL_dKmm, dF_dKmn - dL_dchol = np.dstack([2.*np.dot(dL_dS[:,:,i], L[:,:,i]) for i in range(num_outputs)]) + dL_dchol = 2.*np.array([np.dot(a,b) for a, b in zip(dL_dS, L) ]) dL_dchol = choleskies.triang_to_flat(dL_dchol) grad_dict = {'dL_dKmm':dL_dKmm, 'dL_dKmn':dL_dKmn, 'dL_dKdiag': dF_dv.sum(1), 'dL_dm':dL_dm, 'dL_dchol':dL_dchol, 'dL_dthetaL':dF_dthetaL} if mean_function is not None: grad_dict['dL_dmfZ'] = dF_dmfZ - dKL_dmfZ grad_dict['dL_dmfX'] = dF_dmfX - return Posterior(mean=q_u_mean, cov=S, K=Kmm, prior_mean=prior_mean_u), log_marginal, grad_dict + return Posterior(mean=q_u_mean, cov=S.T, K=Kmm, prior_mean=prior_mean_u), log_marginal, grad_dict diff --git a/GPy/testing/cython_tests.py b/GPy/testing/cython_tests.py index bbc9847d..6c8c4c0f 100644 --- a/GPy/testing/cython_tests.py +++ b/GPy/testing/cython_tests.py @@ -9,8 +9,8 @@ These tests make sure that the opure python and cython codes work the same class CythonTestChols(np.testing.TestCase): def setUp(self): - self.flat = np.random.randn(45, 5) - self.triang = np.dstack([np.eye(20)[:,:,None] for i in range(3)]) + self.flat = np.random.randn(5,45) + self.triang = np.array([np.eye(20) for i in range(3)]) def test_flat_to_triang(self): L1 = choleskies._flat_to_triang_pure(self.flat) L2 = choleskies._flat_to_triang_cython(self.flat) diff --git a/GPy/util/choleskies.py b/GPy/util/choleskies.py index 1844af10..e9731f38 100644 --- a/GPy/util/choleskies.py +++ b/GPy/util/choleskies.py @@ -15,33 +15,33 @@ def safe_root(N): return j def _flat_to_triang_pure(flat_mat): - N, D = flat_mat.shape + D, N = flat_mat.shape M = (-1 + safe_root(8*N+1))//2 - ret = np.zeros((M, M, D)) - count = 0 - for m in range(M): - for mm in range(m+1): - for d in range(D): - ret.flat[d + m*D*M + mm*D] = flat_mat.flat[count]; + ret = np.zeros((D, M, M)) + for d in range(D): + count = 0 + for m in range(M): + for mm in range(m+1): + ret[d,m, mm] = flat_mat[d, count]; count = count+1 return ret def _flat_to_triang_cython(flat_mat): - N, D = flat_mat.shape + D, N = flat_mat.shape M = (-1 + safe_root(8*N+1))//2 return choleskies_cython.flat_to_triang(flat_mat, M) def _triang_to_flat_pure(L): - M, _, D = L.shape + D, _, M = L.shape N = M*(M+1)//2 - flat = np.empty((N, D)) - count = 0; - for m in range(M): - for mm in range(m+1): - for d in range(D): - flat.flat[count] = L.flat[d + m*D*M + mm*D]; + flat = np.empty((D, N)) + for d in range(D): + count = 0; + for m in range(M): + for mm in range(m+1): + flat[d,count] = L[d, m, mm] count = count +1 return flat @@ -74,7 +74,7 @@ def triang_to_cov(L): return np.dstack([np.dot(L[:,:,i], L[:,:,i].T) for i in range(L.shape[-1])]) def multiple_dpotri(Ls): - return np.dstack([linalg.dpotri(np.asfortranarray(Ls[:,:,i]), lower=1)[0] for i in range(Ls.shape[-1])]) + return np.array([linalg.dpotri(np.asfortranarray(Ls[i]), lower=1)[0] for i in range(Ls.shape[0])]) def indexes_to_fix_for_low_rank(rank, size): """ diff --git a/GPy/util/choleskies_cython.c b/GPy/util/choleskies_cython.c index e88b5bf3..d79bdbd1 100644 --- a/GPy/util/choleskies_cython.c +++ b/GPy/util/choleskies_cython.c @@ -1,4 +1,4 @@ -/* Generated by Cython 0.22 */ +/* Generated by Cython 0.21 */ #define PY_SSIZE_T_CLEAN #ifndef CYTHON_USE_PYLONG_INTERNALS @@ -19,7 +19,7 @@ #elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03020000) #error Cython requires Python 2.6+ or Python 3.2+. #else -#define CYTHON_ABI "0_22" +#define CYTHON_ABI "0_21" #include #ifndef offsetof #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) @@ -54,7 +54,7 @@ #define CYTHON_COMPILING_IN_PYPY 0 #define CYTHON_COMPILING_IN_CPYTHON 1 #endif -#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) +#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 #define Py_OptimizeFlag 0 #endif #define __PYX_BUILD_PY_SSIZE_T "n" @@ -73,6 +73,8 @@ #if PY_MAJOR_VERSION >= 3 #define Py_TPFLAGS_CHECKTYPES 0 #define Py_TPFLAGS_HAVE_INDEX 0 +#endif +#if PY_MAJOR_VERSION >= 3 #define Py_TPFLAGS_HAVE_NEWBUFFER 0 #endif #if PY_VERSION_HEX < 0x030400a1 && !defined(Py_TPFLAGS_HAVE_FINALIZE) @@ -99,12 +101,10 @@ #if CYTHON_COMPILING_IN_PYPY #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) - #define __Pyx_PyFrozenSet_Size(s) PyObject_Size(s) #else #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ? \ PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) - #define __Pyx_PyFrozenSet_Size(s) PySet_Size(s) #endif #define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) #define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) @@ -151,11 +151,6 @@ #if PY_MAJOR_VERSION >= 3 #define PyBoolObject PyLongObject #endif -#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY - #ifndef PyUnicode_InternFromString - #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) - #endif -#endif #if PY_VERSION_HEX < 0x030200A4 typedef long Py_hash_t; #define __Pyx_PyInt_FromHash_t PyInt_FromLong @@ -165,9 +160,7 @@ #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t #endif #if PY_MAJOR_VERSION >= 3 - #define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func)) -#else - #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) + #define PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func)) #endif #ifndef CYTHON_INLINE #if defined(__GNUC__) @@ -203,22 +196,11 @@ static CYTHON_INLINE float __PYX_NAN() { return value; } #endif -#define __Pyx_void_to_None(void_result) (void_result, Py_INCREF(Py_None), Py_None) #ifdef __cplusplus template void __Pyx_call_destructor(T* x) { x->~T(); } -template -class __Pyx_FakeReference { - public: - __Pyx_FakeReference() : ptr(NULL) { } - __Pyx_FakeReference(T& ref) : ptr(&ref) { } - T *operator->() { return ptr; } - operator T&() { return *ptr; } - private: - T *ptr; -}; #endif @@ -304,11 +286,11 @@ static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); #endif #define __Pyx_PyObject_AsSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) #define __Pyx_PyObject_AsUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) -#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) -#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) -#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) -#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) -#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) +#define __Pyx_PyObject_FromUString(s) __Pyx_PyObject_FromString((const char*)s) +#define __Pyx_PyBytes_FromUString(s) __Pyx_PyBytes_FromString((const char*)s) +#define __Pyx_PyByteArray_FromUString(s) __Pyx_PyByteArray_FromString((const char*)s) +#define __Pyx_PyStr_FromUString(s) __Pyx_PyStr_FromString((const char*)s) +#define __Pyx_PyUnicode_FromUString(s) __Pyx_PyUnicode_FromString((const char*)s) #if PY_MAJOR_VERSION < 3 static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { @@ -344,7 +326,7 @@ static int __Pyx_init_sys_getdefaultencoding_params(void) { const char* default_encoding_c; sys = PyImport_ImportModule("sys"); if (!sys) goto bad; - default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); + default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL); Py_DECREF(sys); if (!default_encoding) goto bad; default_encoding_c = PyBytes_AsString(default_encoding); @@ -492,7 +474,7 @@ typedef struct { } __Pyx_BufFmt_Context; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":726 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":723 * # in Cython to enable them only on the right systems. * * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< @@ -501,7 +483,7 @@ typedef struct { */ typedef npy_int8 __pyx_t_5numpy_int8_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":727 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":724 * * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< @@ -510,7 +492,7 @@ typedef npy_int8 __pyx_t_5numpy_int8_t; */ typedef npy_int16 __pyx_t_5numpy_int16_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":728 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":725 * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< @@ -519,7 +501,7 @@ typedef npy_int16 __pyx_t_5numpy_int16_t; */ typedef npy_int32 __pyx_t_5numpy_int32_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":729 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":726 * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< @@ -528,7 +510,7 @@ typedef npy_int32 __pyx_t_5numpy_int32_t; */ typedef npy_int64 __pyx_t_5numpy_int64_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":733 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":730 * #ctypedef npy_int128 int128_t * * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< @@ -537,7 +519,7 @@ typedef npy_int64 __pyx_t_5numpy_int64_t; */ typedef npy_uint8 __pyx_t_5numpy_uint8_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":734 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":731 * * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< @@ -546,7 +528,7 @@ typedef npy_uint8 __pyx_t_5numpy_uint8_t; */ typedef npy_uint16 __pyx_t_5numpy_uint16_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":735 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":732 * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< @@ -555,7 +537,7 @@ typedef npy_uint16 __pyx_t_5numpy_uint16_t; */ typedef npy_uint32 __pyx_t_5numpy_uint32_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":736 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":733 * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< @@ -564,7 +546,7 @@ typedef npy_uint32 __pyx_t_5numpy_uint32_t; */ typedef npy_uint64 __pyx_t_5numpy_uint64_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":740 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":737 * #ctypedef npy_uint128 uint128_t * * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< @@ -573,7 +555,7 @@ typedef npy_uint64 __pyx_t_5numpy_uint64_t; */ typedef npy_float32 __pyx_t_5numpy_float32_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":741 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":738 * * ctypedef npy_float32 float32_t * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< @@ -582,7 +564,7 @@ typedef npy_float32 __pyx_t_5numpy_float32_t; */ typedef npy_float64 __pyx_t_5numpy_float64_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":750 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":747 * # The int types are mapped a bit surprising -- * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t # <<<<<<<<<<<<<< @@ -591,7 +573,7 @@ typedef npy_float64 __pyx_t_5numpy_float64_t; */ typedef npy_long __pyx_t_5numpy_int_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":751 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":748 * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< @@ -600,7 +582,7 @@ typedef npy_long __pyx_t_5numpy_int_t; */ typedef npy_longlong __pyx_t_5numpy_long_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":752 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":749 * ctypedef npy_long int_t * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< @@ -609,7 +591,7 @@ typedef npy_longlong __pyx_t_5numpy_long_t; */ typedef npy_longlong __pyx_t_5numpy_longlong_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":754 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":751 * ctypedef npy_longlong longlong_t * * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< @@ -618,7 +600,7 @@ typedef npy_longlong __pyx_t_5numpy_longlong_t; */ typedef npy_ulong __pyx_t_5numpy_uint_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":755 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":752 * * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< @@ -627,7 +609,7 @@ typedef npy_ulong __pyx_t_5numpy_uint_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":756 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":753 * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< @@ -636,7 +618,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":758 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":755 * ctypedef npy_ulonglong ulonglong_t * * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< @@ -645,7 +627,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; */ typedef npy_intp __pyx_t_5numpy_intp_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":759 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":756 * * ctypedef npy_intp intp_t * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< @@ -654,7 +636,7 @@ typedef npy_intp __pyx_t_5numpy_intp_t; */ typedef npy_uintp __pyx_t_5numpy_uintp_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":761 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":758 * ctypedef npy_uintp uintp_t * * ctypedef npy_double float_t # <<<<<<<<<<<<<< @@ -663,7 +645,7 @@ typedef npy_uintp __pyx_t_5numpy_uintp_t; */ typedef npy_double __pyx_t_5numpy_float_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":762 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":759 * * ctypedef npy_double float_t * ctypedef npy_double double_t # <<<<<<<<<<<<<< @@ -672,7 +654,7 @@ typedef npy_double __pyx_t_5numpy_float_t; */ typedef npy_double __pyx_t_5numpy_double_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":763 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":760 * ctypedef npy_double float_t * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< @@ -703,7 +685,7 @@ typedef npy_longdouble __pyx_t_5numpy_longdouble_t; /*--- Type declarations ---*/ -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":765 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":762 * ctypedef npy_longdouble longdouble_t * * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< @@ -712,7 +694,7 @@ typedef npy_longdouble __pyx_t_5numpy_longdouble_t; */ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":766 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":763 * * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< @@ -721,7 +703,7 @@ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; */ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":767 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":764 * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< @@ -730,7 +712,7 @@ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; */ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":769 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":766 * ctypedef npy_clongdouble clongdouble_t * * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< @@ -738,8 +720,6 @@ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; * cdef inline object PyArray_MultiIterNew1(a): */ typedef npy_cdouble __pyx_t_5numpy_complex_t; - -/* --- Runtime support code (head) --- */ #ifndef CYTHON_REFNANNY #define CYTHON_REFNANNY 0 #endif @@ -866,26 +846,6 @@ static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func); static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); -#if PY_MAJOR_VERSION >= 3 -static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key) { - PyObject *value; - value = PyDict_GetItemWithError(d, key); - if (unlikely(!value)) { - if (!PyErr_Occurred()) { - PyObject* args = PyTuple_Pack(1, key); - if (likely(args)) - PyErr_SetObject(PyExc_KeyError, args); - Py_XDECREF(args); - } - return NULL; - } - Py_INCREF(value); - return value; -} -#else - #define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key) -#endif - static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); @@ -1146,7 +1106,7 @@ static char __pyx_k_triang_to_flat[] = "triang_to_flat"; static char __pyx_k_backprop_gradient[] = "backprop_gradient"; static char __pyx_k_GPy_util_choleskies_cython[] = "GPy.util.choleskies_cython"; static char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous"; -static char __pyx_k_home_alans_Work_GPy_GPy_util_ch[] = "/home/alans/Work/GPy/GPy/util/choleskies_cython.pyx"; +static char __pyx_k_home_james_work_GPy_GPy_util_ch[] = "/home/james/work/GPy/GPy/util/choleskies_cython.pyx"; static char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)"; static char __pyx_k_Format_string_allocated_too_shor[] = "Format string allocated too short, see comment in numpy.pxd"; static char __pyx_k_Non_native_byte_order_not_suppor[] = "Non-native byte order not supported"; @@ -1171,7 +1131,7 @@ static PyObject *__pyx_n_s_dL_dK; static PyObject *__pyx_n_s_empty; static PyObject *__pyx_n_s_flat; static PyObject *__pyx_n_s_flat_to_triang; -static PyObject *__pyx_kp_s_home_alans_Work_GPy_GPy_util_ch; +static PyObject *__pyx_kp_s_home_james_work_GPy_GPy_util_ch; static PyObject *__pyx_n_s_i; static PyObject *__pyx_n_s_import; static PyObject *__pyx_n_s_j; @@ -1207,13 +1167,13 @@ static PyObject *__pyx_codeobj__12; * cimport numpy as np * * def flat_to_triang(np.ndarray[double, ndim=2] flat, int M): # <<<<<<<<<<<<<< - * """take a matrix N x D and return a M X M x D array where + * """take a matrix D x N and return a D X M x M array where * */ /* Python wrapper */ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_1flat_to_triang(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -static char __pyx_doc_3GPy_4util_17choleskies_cython_flat_to_triang[] = "take a matrix N x D and return a M X M x D array where\n\n N = M(M+1)/2\n\n the lower triangluar portion of the d'th slice of the result is filled by the d'th column of flat.\n "; +static char __pyx_doc_3GPy_4util_17choleskies_cython_flat_to_triang[] = "take a matrix D x N and return a D X M x M array where\n\n N = M(M+1)/2\n\n the lower triangluar portion of the d'th slice of the result is filled by the d'th column of flat.\n "; static PyMethodDef __pyx_mdef_3GPy_4util_17choleskies_cython_1flat_to_triang = {"flat_to_triang", (PyCFunction)__pyx_pw_3GPy_4util_17choleskies_cython_1flat_to_triang, METH_VARARGS|METH_KEYWORDS, __pyx_doc_3GPy_4util_17choleskies_cython_flat_to_triang}; static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_1flat_to_triang(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { PyArrayObject *__pyx_v_flat = 0; @@ -1280,8 +1240,8 @@ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_1flat_to_triang(PyObjec } static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_flat, int __pyx_v_M) { - CYTHON_UNUSED int __pyx_v_N; int __pyx_v_D; + CYTHON_UNUSED int __pyx_v_N; int __pyx_v_count; PyArrayObject *__pyx_v_ret = 0; int __pyx_v_d; @@ -1332,34 +1292,34 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U /* "GPy/util/choleskies_cython.pyx":17 * the lower triangluar portion of the d'th slice of the result is filled by the d'th column of flat. * """ - * cdef int N = flat.shape[0] # <<<<<<<<<<<<<< - * cdef int D = flat.shape[1] + * cdef int D = flat.shape[0] # <<<<<<<<<<<<<< + * cdef int N = flat.shape[1] * cdef int count = 0 */ - __pyx_v_N = (__pyx_v_flat->dimensions[0]); + __pyx_v_D = (__pyx_v_flat->dimensions[0]); /* "GPy/util/choleskies_cython.pyx":18 * """ - * cdef int N = flat.shape[0] - * cdef int D = flat.shape[1] # <<<<<<<<<<<<<< + * cdef int D = flat.shape[0] + * cdef int N = flat.shape[1] # <<<<<<<<<<<<<< * cdef int count = 0 - * cdef np.ndarray[double, ndim=3] ret = np.zeros((M, M, D)) + * cdef np.ndarray[double, ndim=3] ret = np.zeros((D, M, M)) */ - __pyx_v_D = (__pyx_v_flat->dimensions[1]); + __pyx_v_N = (__pyx_v_flat->dimensions[1]); /* "GPy/util/choleskies_cython.pyx":19 - * cdef int N = flat.shape[0] - * cdef int D = flat.shape[1] + * cdef int D = flat.shape[0] + * cdef int N = flat.shape[1] * cdef int count = 0 # <<<<<<<<<<<<<< - * cdef np.ndarray[double, ndim=3] ret = np.zeros((M, M, D)) + * cdef np.ndarray[double, ndim=3] ret = np.zeros((D, M, M)) * cdef int d, m, mm */ __pyx_v_count = 0; /* "GPy/util/choleskies_cython.pyx":20 - * cdef int D = flat.shape[1] + * cdef int N = flat.shape[1] * cdef int count = 0 - * cdef np.ndarray[double, ndim=3] ret = np.zeros((M, M, D)) # <<<<<<<<<<<<<< + * cdef np.ndarray[double, ndim=3] ret = np.zeros((D, M, M)) # <<<<<<<<<<<<<< * cdef int d, m, mm * for d in range(D): */ @@ -1368,11 +1328,11 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U __pyx_t_3 = __Pyx_PyObject_GetAttrStr(__pyx_t_2, __pyx_n_s_zeros); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - __pyx_t_2 = __Pyx_PyInt_From_int(__pyx_v_M); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = __Pyx_PyInt_From_int(__pyx_v_D); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __pyx_t_4 = __Pyx_PyInt_From_int(__pyx_v_M); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); - __pyx_t_5 = __Pyx_PyInt_From_int(__pyx_v_D); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __Pyx_PyInt_From_int(__pyx_v_M); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); __pyx_t_6 = PyTuple_New(3); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); @@ -1426,7 +1386,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U __pyx_t_1 = 0; /* "GPy/util/choleskies_cython.pyx":22 - * cdef np.ndarray[double, ndim=3] ret = np.zeros((M, M, D)) + * cdef np.ndarray[double, ndim=3] ret = np.zeros((D, M, M)) * cdef int d, m, mm * for d in range(D): # <<<<<<<<<<<<<< * count = 0 @@ -1450,7 +1410,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U * count = 0 * for m in range(M): # <<<<<<<<<<<<<< * for mm in range(m+1): - * ret[m, mm, d] = flat[count,d] + * ret[d, m, mm] = flat[d,count] */ __pyx_t_10 = __pyx_v_M; for (__pyx_t_11 = 0; __pyx_t_11 < __pyx_t_10; __pyx_t_11+=1) { @@ -1460,7 +1420,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U * count = 0 * for m in range(M): * for mm in range(m+1): # <<<<<<<<<<<<<< - * ret[m, mm, d] = flat[count,d] + * ret[d, m, mm] = flat[d,count] * count += 1 */ __pyx_t_12 = (__pyx_v_m + 1); @@ -1470,17 +1430,17 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U /* "GPy/util/choleskies_cython.pyx":26 * for m in range(M): * for mm in range(m+1): - * ret[m, mm, d] = flat[count,d] # <<<<<<<<<<<<<< + * ret[d, m, mm] = flat[d,count] # <<<<<<<<<<<<<< * count += 1 * return ret */ - __pyx_t_14 = __pyx_v_count; - __pyx_t_15 = __pyx_v_d; + __pyx_t_14 = __pyx_v_d; + __pyx_t_15 = __pyx_v_count; if (__pyx_t_14 < 0) __pyx_t_14 += __pyx_pybuffernd_flat.diminfo[0].shape; if (__pyx_t_15 < 0) __pyx_t_15 += __pyx_pybuffernd_flat.diminfo[1].shape; - __pyx_t_16 = __pyx_v_m; - __pyx_t_17 = __pyx_v_mm; - __pyx_t_18 = __pyx_v_d; + __pyx_t_16 = __pyx_v_d; + __pyx_t_17 = __pyx_v_m; + __pyx_t_18 = __pyx_v_mm; if (__pyx_t_16 < 0) __pyx_t_16 += __pyx_pybuffernd_ret.diminfo[0].shape; if (__pyx_t_17 < 0) __pyx_t_17 += __pyx_pybuffernd_ret.diminfo[1].shape; if (__pyx_t_18 < 0) __pyx_t_18 += __pyx_pybuffernd_ret.diminfo[2].shape; @@ -1488,7 +1448,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U /* "GPy/util/choleskies_cython.pyx":27 * for mm in range(m+1): - * ret[m, mm, d] = flat[count,d] + * ret[d, m, mm] = flat[d,count] * count += 1 # <<<<<<<<<<<<<< * return ret * @@ -1499,7 +1459,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U } /* "GPy/util/choleskies_cython.pyx":28 - * ret[m, mm, d] = flat[count,d] + * ret[d, m, mm] = flat[d,count] * count += 1 * return ret # <<<<<<<<<<<<<< * @@ -1514,7 +1474,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U * cimport numpy as np * * def flat_to_triang(np.ndarray[double, ndim=2] flat, int M): # <<<<<<<<<<<<<< - * """take a matrix N x D and return a M X M x D array where + * """take a matrix D x N and return a D X M x M array where * */ @@ -1548,8 +1508,8 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U * return ret * * def triang_to_flat(np.ndarray[double, ndim=3] L): # <<<<<<<<<<<<<< - * cdef int M = L.shape[0] - * cdef int D = L.shape[2] + * cdef int D = L.shape[0] + * cdef int M = L.shape[1] */ /* Python wrapper */ @@ -1575,8 +1535,8 @@ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_3triang_to_flat(PyObjec } static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_L) { - int __pyx_v_M; int __pyx_v_D; + int __pyx_v_M; int __pyx_v_N; int __pyx_v_count; PyArrayObject *__pyx_v_flat = 0; @@ -1627,35 +1587,35 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ /* "GPy/util/choleskies_cython.pyx":31 * * def triang_to_flat(np.ndarray[double, ndim=3] L): - * cdef int M = L.shape[0] # <<<<<<<<<<<<<< - * cdef int D = L.shape[2] + * cdef int D = L.shape[0] # <<<<<<<<<<<<<< + * cdef int M = L.shape[1] * cdef int N = M*(M+1)/2 */ - __pyx_v_M = (__pyx_v_L->dimensions[0]); + __pyx_v_D = (__pyx_v_L->dimensions[0]); /* "GPy/util/choleskies_cython.pyx":32 * def triang_to_flat(np.ndarray[double, ndim=3] L): - * cdef int M = L.shape[0] - * cdef int D = L.shape[2] # <<<<<<<<<<<<<< + * cdef int D = L.shape[0] + * cdef int M = L.shape[1] # <<<<<<<<<<<<<< * cdef int N = M*(M+1)/2 * cdef int count = 0 */ - __pyx_v_D = (__pyx_v_L->dimensions[2]); + __pyx_v_M = (__pyx_v_L->dimensions[1]); /* "GPy/util/choleskies_cython.pyx":33 - * cdef int M = L.shape[0] - * cdef int D = L.shape[2] + * cdef int D = L.shape[0] + * cdef int M = L.shape[1] * cdef int N = M*(M+1)/2 # <<<<<<<<<<<<<< * cdef int count = 0 - * cdef np.ndarray[double, ndim=2] flat = np.empty((N, D)) + * cdef np.ndarray[double, ndim=2] flat = np.empty((D, N)) */ __pyx_v_N = __Pyx_div_long((__pyx_v_M * (__pyx_v_M + 1)), 2); /* "GPy/util/choleskies_cython.pyx":34 - * cdef int D = L.shape[2] + * cdef int M = L.shape[1] * cdef int N = M*(M+1)/2 * cdef int count = 0 # <<<<<<<<<<<<<< - * cdef np.ndarray[double, ndim=2] flat = np.empty((N, D)) + * cdef np.ndarray[double, ndim=2] flat = np.empty((D, N)) * cdef int d, m, mm */ __pyx_v_count = 0; @@ -1663,7 +1623,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ /* "GPy/util/choleskies_cython.pyx":35 * cdef int N = M*(M+1)/2 * cdef int count = 0 - * cdef np.ndarray[double, ndim=2] flat = np.empty((N, D)) # <<<<<<<<<<<<<< + * cdef np.ndarray[double, ndim=2] flat = np.empty((D, N)) # <<<<<<<<<<<<<< * cdef int d, m, mm * for d in range(D): */ @@ -1672,9 +1632,9 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ __pyx_t_3 = __Pyx_PyObject_GetAttrStr(__pyx_t_2, __pyx_n_s_empty); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 35; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - __pyx_t_2 = __Pyx_PyInt_From_int(__pyx_v_N); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 35; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = __Pyx_PyInt_From_int(__pyx_v_D); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 35; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); - __pyx_t_4 = __Pyx_PyInt_From_int(__pyx_v_D); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 35; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_int(__pyx_v_N); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 35; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_5 = PyTuple_New(2); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 35; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); @@ -1725,7 +1685,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ __pyx_t_1 = 0; /* "GPy/util/choleskies_cython.pyx":37 - * cdef np.ndarray[double, ndim=2] flat = np.empty((N, D)) + * cdef np.ndarray[double, ndim=2] flat = np.empty((D, N)) * cdef int d, m, mm * for d in range(D): # <<<<<<<<<<<<<< * count = 0 @@ -1749,7 +1709,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ * count = 0 * for m in range(M): # <<<<<<<<<<<<<< * for mm in range(m+1): - * flat[count,d] = L[m, mm, d] + * flat[d,count] = L[d, m, mm] */ __pyx_t_9 = __pyx_v_M; for (__pyx_t_10 = 0; __pyx_t_10 < __pyx_t_9; __pyx_t_10+=1) { @@ -1759,7 +1719,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ * count = 0 * for m in range(M): * for mm in range(m+1): # <<<<<<<<<<<<<< - * flat[count,d] = L[m, mm, d] + * flat[d,count] = L[d, m, mm] * count += 1 */ __pyx_t_11 = (__pyx_v_m + 1); @@ -1769,25 +1729,25 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ /* "GPy/util/choleskies_cython.pyx":41 * for m in range(M): * for mm in range(m+1): - * flat[count,d] = L[m, mm, d] # <<<<<<<<<<<<<< + * flat[d,count] = L[d, m, mm] # <<<<<<<<<<<<<< * count += 1 * return flat */ - __pyx_t_13 = __pyx_v_m; - __pyx_t_14 = __pyx_v_mm; - __pyx_t_15 = __pyx_v_d; + __pyx_t_13 = __pyx_v_d; + __pyx_t_14 = __pyx_v_m; + __pyx_t_15 = __pyx_v_mm; if (__pyx_t_13 < 0) __pyx_t_13 += __pyx_pybuffernd_L.diminfo[0].shape; if (__pyx_t_14 < 0) __pyx_t_14 += __pyx_pybuffernd_L.diminfo[1].shape; if (__pyx_t_15 < 0) __pyx_t_15 += __pyx_pybuffernd_L.diminfo[2].shape; - __pyx_t_16 = __pyx_v_count; - __pyx_t_17 = __pyx_v_d; + __pyx_t_16 = __pyx_v_d; + __pyx_t_17 = __pyx_v_count; if (__pyx_t_16 < 0) __pyx_t_16 += __pyx_pybuffernd_flat.diminfo[0].shape; if (__pyx_t_17 < 0) __pyx_t_17 += __pyx_pybuffernd_flat.diminfo[1].shape; *__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_flat.rcbuffer->pybuffer.buf, __pyx_t_16, __pyx_pybuffernd_flat.diminfo[0].strides, __pyx_t_17, __pyx_pybuffernd_flat.diminfo[1].strides) = (*__Pyx_BufPtrStrided3d(double *, __pyx_pybuffernd_L.rcbuffer->pybuffer.buf, __pyx_t_13, __pyx_pybuffernd_L.diminfo[0].strides, __pyx_t_14, __pyx_pybuffernd_L.diminfo[1].strides, __pyx_t_15, __pyx_pybuffernd_L.diminfo[2].strides)); /* "GPy/util/choleskies_cython.pyx":42 * for mm in range(m+1): - * flat[count,d] = L[m, mm, d] + * flat[d,count] = L[d, m, mm] * count += 1 # <<<<<<<<<<<<<< * return flat * @@ -1798,7 +1758,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ } /* "GPy/util/choleskies_cython.pyx":43 - * flat[count,d] = L[m, mm, d] + * flat[d,count] = L[d, m, mm] * count += 1 * return flat # <<<<<<<<<<<<<< * @@ -1813,8 +1773,8 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ * return ret * * def triang_to_flat(np.ndarray[double, ndim=3] L): # <<<<<<<<<<<<<< - * cdef int M = L.shape[0] - * cdef int D = L.shape[2] + * cdef int D = L.shape[0] + * cdef int M = L.shape[1] */ /* function exit code */ @@ -2261,7 +2221,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_4backprop_gradient(CYTH return __pyx_r; } -/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":197 +/* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":194 * # experimental exception made for __getbuffer__ and __releasebuffer__ * # -- the details of this may change. * def __getbuffer__(ndarray self, Py_buffer* info, int flags): # <<<<<<<<<<<<<< @@ -2311,7 +2271,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __Pyx_GIVEREF(__pyx_v_info->obj); } - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":203 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":200 * # of flags * * if info == NULL: return # <<<<<<<<<<<<<< @@ -2324,7 +2284,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P goto __pyx_L0; } - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":206 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":203 * * cdef int copy_shape, i, ndim * cdef int endian_detector = 1 # <<<<<<<<<<<<<< @@ -2333,7 +2293,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_endian_detector = 1; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":207 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":204 * cdef int copy_shape, i, ndim * cdef int endian_detector = 1 * cdef bint little_endian = ((&endian_detector)[0] != 0) # <<<<<<<<<<<<<< @@ -2342,7 +2302,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_little_endian = ((((char *)(&__pyx_v_endian_detector))[0]) != 0); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":209 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":206 * cdef bint little_endian = ((&endian_detector)[0] != 0) * * ndim = PyArray_NDIM(self) # <<<<<<<<<<<<<< @@ -2351,7 +2311,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_ndim = PyArray_NDIM(__pyx_v_self); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":211 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":208 * ndim = PyArray_NDIM(self) * * if sizeof(npy_intp) != sizeof(Py_ssize_t): # <<<<<<<<<<<<<< @@ -2361,7 +2321,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_1 = (((sizeof(npy_intp)) != (sizeof(Py_ssize_t))) != 0); if (__pyx_t_1) { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":212 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":209 * * if sizeof(npy_intp) != sizeof(Py_ssize_t): * copy_shape = 1 # <<<<<<<<<<<<<< @@ -2373,7 +2333,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } /*else*/ { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":214 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":211 * copy_shape = 1 * else: * copy_shape = 0 # <<<<<<<<<<<<<< @@ -2384,7 +2344,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } __pyx_L4:; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":216 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":213 * copy_shape = 0 * * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) # <<<<<<<<<<<<<< @@ -2393,12 +2353,14 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = (((__pyx_v_flags & PyBUF_C_CONTIGUOUS) == PyBUF_C_CONTIGUOUS) != 0); if (__pyx_t_2) { + goto __pyx_L7_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L6_bool_binop_done; } + __pyx_L7_next_and:; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":217 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":214 * * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): # <<<<<<<<<<<<<< @@ -2410,21 +2372,21 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_L6_bool_binop_done:; if (__pyx_t_1) { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":218 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":215 * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): * raise ValueError(u"ndarray is not C contiguous") # <<<<<<<<<<<<<< * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) */ - __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple_, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 218; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple_, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - {__pyx_filename = __pyx_f[1]; __pyx_lineno = 218; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":220 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":217 * raise ValueError(u"ndarray is not C contiguous") * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) # <<<<<<<<<<<<<< @@ -2433,12 +2395,14 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = (((__pyx_v_flags & PyBUF_F_CONTIGUOUS) == PyBUF_F_CONTIGUOUS) != 0); if (__pyx_t_2) { + goto __pyx_L10_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L9_bool_binop_done; } + __pyx_L10_next_and:; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":221 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":218 * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): # <<<<<<<<<<<<<< @@ -2450,21 +2414,21 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_L9_bool_binop_done:; if (__pyx_t_1) { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":222 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":219 * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): * raise ValueError(u"ndarray is not Fortran contiguous") # <<<<<<<<<<<<<< * * info.buf = PyArray_DATA(self) */ - __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__2, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 222; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__2, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - {__pyx_filename = __pyx_f[1]; __pyx_lineno = 222; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":224 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":221 * raise ValueError(u"ndarray is not Fortran contiguous") * * info.buf = PyArray_DATA(self) # <<<<<<<<<<<<<< @@ -2473,7 +2437,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->buf = PyArray_DATA(__pyx_v_self); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":225 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":222 * * info.buf = PyArray_DATA(self) * info.ndim = ndim # <<<<<<<<<<<<<< @@ -2482,7 +2446,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->ndim = __pyx_v_ndim; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":226 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":223 * info.buf = PyArray_DATA(self) * info.ndim = ndim * if copy_shape: # <<<<<<<<<<<<<< @@ -2492,7 +2456,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_1 = (__pyx_v_copy_shape != 0); if (__pyx_t_1) { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":229 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":226 * # Allocate new buffer for strides and shape info. * # This is allocated as one block, strides first. * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) # <<<<<<<<<<<<<< @@ -2501,7 +2465,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->strides = ((Py_ssize_t *)malloc((((sizeof(Py_ssize_t)) * ((size_t)__pyx_v_ndim)) * 2))); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":230 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":227 * # This is allocated as one block, strides first. * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) * info.shape = info.strides + ndim # <<<<<<<<<<<<<< @@ -2510,7 +2474,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->shape = (__pyx_v_info->strides + __pyx_v_ndim); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":231 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":228 * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) * info.shape = info.strides + ndim * for i in range(ndim): # <<<<<<<<<<<<<< @@ -2521,7 +2485,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":232 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":229 * info.shape = info.strides + ndim * for i in range(ndim): * info.strides[i] = PyArray_STRIDES(self)[i] # <<<<<<<<<<<<<< @@ -2530,7 +2494,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ (__pyx_v_info->strides[__pyx_v_i]) = (PyArray_STRIDES(__pyx_v_self)[__pyx_v_i]); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":233 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":230 * for i in range(ndim): * info.strides[i] = PyArray_STRIDES(self)[i] * info.shape[i] = PyArray_DIMS(self)[i] # <<<<<<<<<<<<<< @@ -2543,7 +2507,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } /*else*/ { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":235 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":232 * info.shape[i] = PyArray_DIMS(self)[i] * else: * info.strides = PyArray_STRIDES(self) # <<<<<<<<<<<<<< @@ -2552,7 +2516,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->strides = ((Py_ssize_t *)PyArray_STRIDES(__pyx_v_self)); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":236 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":233 * else: * info.strides = PyArray_STRIDES(self) * info.shape = PyArray_DIMS(self) # <<<<<<<<<<<<<< @@ -2563,7 +2527,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } __pyx_L11:; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":237 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":234 * info.strides = PyArray_STRIDES(self) * info.shape = PyArray_DIMS(self) * info.suboffsets = NULL # <<<<<<<<<<<<<< @@ -2572,7 +2536,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->suboffsets = NULL; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":238 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":235 * info.shape = PyArray_DIMS(self) * info.suboffsets = NULL * info.itemsize = PyArray_ITEMSIZE(self) # <<<<<<<<<<<<<< @@ -2581,7 +2545,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->itemsize = PyArray_ITEMSIZE(__pyx_v_self); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":239 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":236 * info.suboffsets = NULL * info.itemsize = PyArray_ITEMSIZE(self) * info.readonly = not PyArray_ISWRITEABLE(self) # <<<<<<<<<<<<<< @@ -2590,7 +2554,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->readonly = (!(PyArray_ISWRITEABLE(__pyx_v_self) != 0)); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":242 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":239 * * cdef int t * cdef char* f = NULL # <<<<<<<<<<<<<< @@ -2599,7 +2563,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_f = NULL; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":243 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":240 * cdef int t * cdef char* f = NULL * cdef dtype descr = self.descr # <<<<<<<<<<<<<< @@ -2611,7 +2575,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_descr = ((PyArray_Descr *)__pyx_t_3); __pyx_t_3 = 0; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":247 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":244 * cdef int offset * * cdef bint hasfields = PyDataType_HASFIELDS(descr) # <<<<<<<<<<<<<< @@ -2620,7 +2584,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_hasfields = PyDataType_HASFIELDS(__pyx_v_descr); - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":249 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":246 * cdef bint hasfields = PyDataType_HASFIELDS(descr) * * if not hasfields and not copy_shape: # <<<<<<<<<<<<<< @@ -2629,16 +2593,18 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = ((!(__pyx_v_hasfields != 0)) != 0); if (__pyx_t_2) { + goto __pyx_L16_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L15_bool_binop_done; } + __pyx_L16_next_and:; __pyx_t_2 = ((!(__pyx_v_copy_shape != 0)) != 0); __pyx_t_1 = __pyx_t_2; __pyx_L15_bool_binop_done:; if (__pyx_t_1) { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":251 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":248 * if not hasfields and not copy_shape: * # do not call releasebuffer * info.obj = None # <<<<<<<<<<<<<< @@ -2654,7 +2620,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } /*else*/ { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":254 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":251 * else: * # need to call releasebuffer * info.obj = self # <<<<<<<<<<<<<< @@ -2669,7 +2635,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } __pyx_L14:; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":256 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":253 * info.obj = self * * if not hasfields: # <<<<<<<<<<<<<< @@ -2679,7 +2645,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_1 = ((!(__pyx_v_hasfields != 0)) != 0); if (__pyx_t_1) { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":254 * * if not hasfields: * t = descr.type_num # <<<<<<<<<<<<<< @@ -2689,7 +2655,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_4 = __pyx_v_descr->type_num; __pyx_v_t = __pyx_t_4; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":258 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":255 * if not hasfields: * t = descr.type_num * if ((descr.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< @@ -2700,16 +2666,19 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P if (!__pyx_t_2) { goto __pyx_L20_next_or; } else { + goto __pyx_L21_next_and; } + __pyx_L21_next_and:; __pyx_t_2 = (__pyx_v_little_endian != 0); if (!__pyx_t_2) { + goto __pyx_L20_next_or; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L19_bool_binop_done; } __pyx_L20_next_or:; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":259 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":256 * t = descr.type_num * if ((descr.byteorder == c'>' and little_endian) or * (descr.byteorder == c'<' and not little_endian)): # <<<<<<<<<<<<<< @@ -2718,30 +2687,32 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_t_2 = ((__pyx_v_descr->byteorder == '<') != 0); if (__pyx_t_2) { + goto __pyx_L22_next_and; } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L19_bool_binop_done; } + __pyx_L22_next_and:; __pyx_t_2 = ((!(__pyx_v_little_endian != 0)) != 0); __pyx_t_1 = __pyx_t_2; __pyx_L19_bool_binop_done:; if (__pyx_t_1) { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":260 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 * if ((descr.byteorder == c'>' and little_endian) or * (descr.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<< * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" */ - __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__3, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 260; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__3, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_Raise(__pyx_t_3, 0, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - {__pyx_filename = __pyx_f[1]; __pyx_lineno = 260; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[1]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":277 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274 * elif t == NPY_CDOUBLE: f = "Zd" * elif t == NPY_CLONGDOUBLE: f = "Zg" * elif t == NPY_OBJECT: f = "O" # <<<<<<<<<<<<<< @@ -2750,7 +2721,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ switch (__pyx_v_t) { - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":261 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":258 * (descr.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") * if t == NPY_BYTE: f = "b" # <<<<<<<<<<<<<< @@ -2761,7 +2732,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_b; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":262 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":259 * raise ValueError(u"Non-native byte order not supported") * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" # <<<<<<<<<<<<<< @@ -2772,7 +2743,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_B; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":263 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":260 * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" * elif t == NPY_SHORT: f = "h" # <<<<<<<<<<<<<< @@ -2783,7 +2754,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_h; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":264 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":261 * elif t == NPY_UBYTE: f = "B" * elif t == NPY_SHORT: f = "h" * elif t == NPY_USHORT: f = "H" # <<<<<<<<<<<<<< @@ -2794,7 +2765,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_H; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":265 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":262 * elif t == NPY_SHORT: f = "h" * elif t == NPY_USHORT: f = "H" * elif t == NPY_INT: f = "i" # <<<<<<<<<<<<<< @@ -2805,7 +2776,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_i; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":266 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":263 * elif t == NPY_USHORT: f = "H" * elif t == NPY_INT: f = "i" * elif t == NPY_UINT: f = "I" # <<<<<<<<<<<<<< @@ -2816,7 +2787,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_I; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":267 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":264 * elif t == NPY_INT: f = "i" * elif t == NPY_UINT: f = "I" * elif t == NPY_LONG: f = "l" # <<<<<<<<<<<<<< @@ -2827,7 +2798,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_l; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":268 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":265 * elif t == NPY_UINT: f = "I" * elif t == NPY_LONG: f = "l" * elif t == NPY_ULONG: f = "L" # <<<<<<<<<<<<<< @@ -2838,7 +2809,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_L; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":269 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":266 * elif t == NPY_LONG: f = "l" * elif t == NPY_ULONG: f = "L" * elif t == NPY_LONGLONG: f = "q" # <<<<<<<<<<<<<< @@ -2849,7 +2820,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_q; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":270 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":267 * elif t == NPY_ULONG: f = "L" * elif t == NPY_LONGLONG: f = "q" * elif t == NPY_ULONGLONG: f = "Q" # <<<<<<<<<<<<<< @@ -2860,7 +2831,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Q; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":271 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":268 * elif t == NPY_LONGLONG: f = "q" * elif t == NPY_ULONGLONG: f = "Q" * elif t == NPY_FLOAT: f = "f" # <<<<<<<<<<<<<< @@ -2871,7 +2842,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_f; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":272 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":269 * elif t == NPY_ULONGLONG: f = "Q" * elif t == NPY_FLOAT: f = "f" * elif t == NPY_DOUBLE: f = "d" # <<<<<<<<<<<<<< @@ -2882,7 +2853,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_d; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":273 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":270 * elif t == NPY_FLOAT: f = "f" * elif t == NPY_DOUBLE: f = "d" * elif t == NPY_LONGDOUBLE: f = "g" # <<<<<<<<<<<<<< @@ -2893,7 +2864,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_g; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":271 * elif t == NPY_DOUBLE: f = "d" * elif t == NPY_LONGDOUBLE: f = "g" * elif t == NPY_CFLOAT: f = "Zf" # <<<<<<<<<<<<<< @@ -2904,7 +2875,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zf; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":275 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":272 * elif t == NPY_LONGDOUBLE: f = "g" * elif t == NPY_CFLOAT: f = "Zf" * elif t == NPY_CDOUBLE: f = "Zd" # <<<<<<<<<<<<<< @@ -2915,7 +2886,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zd; break; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":276 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":273 * elif t == NPY_CFLOAT: f = "Zf" * elif t == NPY_CDOUBLE: f = "Zd" * elif t == NPY_CLONGDOUBLE: f = "Zg" # <<<<<<<<<<<<<< @@ -2926,7 +2897,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zg; 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if (unlikely(!__pyx_tuple__9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_tuple__9 = PyTuple_Pack(9, __pyx_n_s_L, __pyx_n_s_D, __pyx_n_s_M, __pyx_n_s_N, __pyx_n_s_count, __pyx_n_s_flat, __pyx_n_s_d, __pyx_n_s_m, __pyx_n_s_mm); if (unlikely(!__pyx_tuple__9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_tuple__9); __Pyx_GIVEREF(__pyx_tuple__9); - __pyx_codeobj__10 = (PyObject*)__Pyx_PyCode_New(1, 0, 9, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__9, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_home_alans_Work_GPy_GPy_util_ch, __pyx_n_s_triang_to_flat, 30, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_codeobj__10 = (PyObject*)__Pyx_PyCode_New(1, 0, 9, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__9, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_home_james_work_GPy_GPy_util_ch, __pyx_n_s_triang_to_flat, 30, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L1_error;} /* "GPy/util/choleskies_cython.pyx":46 * @@ -4439,7 +4411,7 @@ static int __Pyx_InitCachedConstants(void) { __pyx_tuple__11 = PyTuple_Pack(7, __pyx_n_s_dL, __pyx_n_s_L, __pyx_n_s_dL_dK, __pyx_n_s_N, __pyx_n_s_k, __pyx_n_s_j, __pyx_n_s_i); if (unlikely(!__pyx_tuple__11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_tuple__11); __Pyx_GIVEREF(__pyx_tuple__11); - __pyx_codeobj__12 = (PyObject*)__Pyx_PyCode_New(2, 0, 7, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__11, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_home_alans_Work_GPy_GPy_util_ch, __pyx_n_s_backprop_gradient, 46, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__12)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_codeobj__12 = (PyObject*)__Pyx_PyCode_New(2, 0, 7, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__11, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_home_james_work_GPy_GPy_util_ch, __pyx_n_s_backprop_gradient, 46, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__12)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_RefNannyFinishContext(); return 0; __pyx_L1_error:; @@ -4543,10 +4515,10 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void) #endif 0); if (unlikely(!__pyx_ptype_7cpython_4type_type)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 9; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_ptype_5numpy_dtype = __Pyx_ImportType("numpy", "dtype", sizeof(PyArray_Descr), 0); if (unlikely(!__pyx_ptype_5numpy_dtype)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 155; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_ptype_5numpy_flatiter = __Pyx_ImportType("numpy", "flatiter", sizeof(PyArrayIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_flatiter)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 168; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_ptype_5numpy_broadcast = __Pyx_ImportType("numpy", "broadcast", sizeof(PyArrayMultiIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_broadcast)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 172; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_ptype_5numpy_ndarray = __Pyx_ImportType("numpy", "ndarray", sizeof(PyArrayObject), 0); if (unlikely(!__pyx_ptype_5numpy_ndarray)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 181; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_ptype_5numpy_ufunc = __Pyx_ImportType("numpy", "ufunc", sizeof(PyUFuncObject), 0); if (unlikely(!__pyx_ptype_5numpy_ufunc)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 864; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_ptype_5numpy_flatiter = __Pyx_ImportType("numpy", "flatiter", sizeof(PyArrayIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_flatiter)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 165; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_ptype_5numpy_broadcast = __Pyx_ImportType("numpy", "broadcast", sizeof(PyArrayMultiIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_broadcast)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 169; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_ptype_5numpy_ndarray = __Pyx_ImportType("numpy", "ndarray", sizeof(PyArrayObject), 0); if (unlikely(!__pyx_ptype_5numpy_ndarray)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_ptype_5numpy_ufunc = __Pyx_ImportType("numpy", "ufunc", sizeof(PyUFuncObject), 0); if (unlikely(!__pyx_ptype_5numpy_ufunc)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 861; __pyx_clineno = __LINE__; goto __pyx_L1_error;} /*--- Variable import code ---*/ /*--- Function import code ---*/ /*--- Execution code ---*/ @@ -4567,7 +4539,7 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void) * cimport numpy as np * * def flat_to_triang(np.ndarray[double, ndim=2] flat, int M): # <<<<<<<<<<<<<< - * """take a matrix N x D and return a M X M x D array where + * """take a matrix D x N and return a D X M x M array where * */ __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_17choleskies_cython_1flat_to_triang, NULL, __pyx_n_s_GPy_util_choleskies_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 10; __pyx_clineno = __LINE__; goto __pyx_L1_error;} @@ -4579,8 +4551,8 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void) * return ret * * def triang_to_flat(np.ndarray[double, ndim=3] L): # <<<<<<<<<<<<<< - * cdef int M = L.shape[0] - * cdef int D = L.shape[2] + * cdef int D = L.shape[0] + * cdef int M = L.shape[1] */ __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_17choleskies_cython_3triang_to_flat, NULL, __pyx_n_s_GPy_util_choleskies_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); @@ -4609,7 +4581,7 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void) if (PyDict_SetItem(__pyx_d, __pyx_n_s_test, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":979 + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":976 * arr.base = baseptr * * cdef inline object get_array_base(ndarray arr): # <<<<<<<<<<<<<< @@ -4625,6 +4597,7 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void) if (__pyx_m) { if (__pyx_d) { __Pyx_AddTraceback("init GPy.util.choleskies_cython", __pyx_clineno, __pyx_lineno, __pyx_filename); + Py_DECREF(__pyx_d); __pyx_d = 0; } Py_DECREF(__pyx_m); __pyx_m = 0; } else if (!PyErr_Occurred()) { @@ -4639,7 +4612,7 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void) #endif } -/* --- Runtime support code --- */ +/* Runtime support code */ #if CYTHON_REFNANNY static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname) { PyObject *m = NULL, *p = NULL; @@ -5668,13 +5641,6 @@ static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject } PyErr_SetObject(type, value); if (tb) { -#if CYTHON_COMPILING_IN_PYPY - PyObject *tmp_type, *tmp_value, *tmp_tb; - PyErr_Fetch(tmp_type, tmp_value, tmp_tb); - Py_INCREF(tb); - PyErr_Restore(tmp_type, tmp_value, tb); - Py_XDECREF(tmp_tb); -#else PyThreadState *tstate = PyThreadState_GET(); PyObject* tmp_tb = tstate->curexc_traceback; if (tb != tmp_tb) { @@ -5682,7 +5648,6 @@ static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject tstate->curexc_traceback = tb; Py_XDECREF(tmp_tb); } -#endif } bad: Py_XDECREF(owned_instance); diff --git a/GPy/util/choleskies_cython.pyx b/GPy/util/choleskies_cython.pyx index 7217f962..13f8c8ae 100644 --- a/GPy/util/choleskies_cython.pyx +++ b/GPy/util/choleskies_cython.pyx @@ -8,37 +8,37 @@ import numpy as np cimport numpy as np def flat_to_triang(np.ndarray[double, ndim=2] flat, int M): - """take a matrix N x D and return a M X M x D array where + """take a matrix D x N and return a D X M x M array where N = M(M+1)/2 the lower triangluar portion of the d'th slice of the result is filled by the d'th column of flat. """ - cdef int N = flat.shape[0] - cdef int D = flat.shape[1] + cdef int D = flat.shape[0] + cdef int N = flat.shape[1] cdef int count = 0 - cdef np.ndarray[double, ndim=3] ret = np.zeros((M, M, D)) + cdef np.ndarray[double, ndim=3] ret = np.zeros((D, M, M)) cdef int d, m, mm for d in range(D): count = 0 for m in range(M): for mm in range(m+1): - ret[m, mm, d] = flat[count,d] + ret[d, m, mm] = flat[d,count] count += 1 return ret def triang_to_flat(np.ndarray[double, ndim=3] L): - cdef int M = L.shape[0] - cdef int D = L.shape[2] + cdef int D = L.shape[0] + cdef int M = L.shape[1] cdef int N = M*(M+1)/2 cdef int count = 0 - cdef np.ndarray[double, ndim=2] flat = np.empty((N, D)) + cdef np.ndarray[double, ndim=2] flat = np.empty((D, N)) cdef int d, m, mm for d in range(D): count = 0 for m in range(M): for mm in range(m+1): - flat[count,d] = L[m, mm, d] + flat[d,count] = L[d, m, mm] count += 1 return flat From 0450e228a8edf364d9fa328285c0c56e7d511194 Mon Sep 17 00:00:00 2001 From: James Hensman Date: Tue, 5 May 2015 14:29:07 +0100 Subject: [PATCH 02/41] svgp tests are passing with re-ordered chols --- GPy/inference/latent_function_inference/svgp.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/GPy/inference/latent_function_inference/svgp.py b/GPy/inference/latent_function_inference/svgp.py index 261a68b6..b23a09b0 100644 --- a/GPy/inference/latent_function_inference/svgp.py +++ b/GPy/inference/latent_function_inference/svgp.py @@ -100,10 +100,8 @@ class SVGP(LatentFunctionInference): #sum (gradients of) expected likelihood and KL part - log_marginal = F.sum() - dL_dm, dL_dS, dL_dKmm, dL_dKmn = dF_dm - dKL_dm*0, dF_dS- dKL_dS*0, dF_dKmm- dKL_dKmm*0, dF_dKmn - #log_marginal = F.sum() - KL - #dL_dm, dL_dS, dL_dKmm, dL_dKmn = dF_dm - dKL_dm, dF_dS- dKL_dS, dF_dKmm- dKL_dKmm, dF_dKmn + log_marginal = F.sum() - KL + dL_dm, dL_dS, dL_dKmm, dL_dKmn = dF_dm - dKL_dm, dF_dS- dKL_dS, dF_dKmm- dKL_dKmm, dF_dKmn dL_dchol = 2.*np.array([np.dot(a,b) for a, b in zip(dL_dS, L) ]) dL_dchol = choleskies.triang_to_flat(dL_dchol) From dc138aa97b54ddc9c2da6c610f25f4ab7af12907 Mon Sep 17 00:00:00 2001 From: Max Zwiessele Date: Mon, 11 May 2015 11:21:45 +0100 Subject: [PATCH 03/41] [predict] documentation --- GPy/core/gp.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 4b6231af..3acea54b 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -229,13 +229,14 @@ class GP(Model): :param Y_metadata: metadata about the predicting point to pass to the likelihood :param kern: The kernel to use for prediction (defaults to the model kern). this is useful for examining e.g. subprocesses. - :returns: (mean, var, lower_upper): + :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 - lower_upper: lower and upper boundaries of the 95% confidence intervals, Numpy arrays, Nnew x self.input_dim 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. + + Note: If you want the predictive quantiles (e.g. 95% confidence interval) use :py:func:~GPy.core.gp.GP.predict_quantiles. """ #predict the latent function values mu, var = self._raw_predict(Xnew, full_cov=full_cov, kern=kern) @@ -255,7 +256,7 @@ class GP(Model): :param quantiles: tuple of quantiles, default is (2.5, 97.5) which is the 95% interval :type quantiles: tuple :returns: list of quantiles for each X and predictive quantiles for interval combination - :rtype: [np.ndarray (Xnew x self.input_dim), np.ndarray (Xnew x self.input_dim)] + :rtype: [np.ndarray (Xnew x self.output_dim), np.ndarray (Xnew x self.output_dim)] """ m, v = self._raw_predict(X, full_cov=False) if self.normalizer is not None: From b55f84f04f6fd5bcbca27e854a77218db5cb3b84 Mon Sep 17 00:00:00 2001 From: Max Zwiessele Date: Mon, 11 May 2015 11:26:25 +0100 Subject: [PATCH 04/41] [predict] documentation --- 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 3acea54b..c2d2010c 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -236,7 +236,7 @@ class GP(Model): 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. - Note: If you want the predictive quantiles (e.g. 95% confidence interval) use :py:func:~GPy.core.gp.GP.predict_quantiles. + Note: If you want the predictive quantiles (e.g. 95% confidence interval) use :py:func:"~GPy.core.gp.GP.predict_quantiles". """ #predict the latent function values mu, var = self._raw_predict(Xnew, full_cov=full_cov, kern=kern) From 16296626787466a179f05a7b50041ff72ec0a731 Mon Sep 17 00:00:00 2001 From: Max Zwiessele Date: Thu, 14 May 2015 11:18:40 +0100 Subject: [PATCH 05/41] [cython import] error notices where it happens --- GPy/kern/_src/stationary.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/kern/_src/stationary.py b/GPy/kern/_src/stationary.py index b5e425e6..df064de7 100644 --- a/GPy/kern/_src/stationary.py +++ b/GPy/kern/_src/stationary.py @@ -15,7 +15,7 @@ from ...util.caching import Cache_this try: import stationary_cython except ImportError: - print('warning: failed to import cython module: falling back to numpy') + print('warning in sationary: failed to import cython module: falling back to numpy') config.set('cython', 'working', 'false') From 466b381443346405fc557866d02538f6b37669e1 Mon Sep 17 00:00:00 2001 From: Max Zwiessele Date: Thu, 14 May 2015 11:21:14 +0100 Subject: [PATCH 06/41] [opt messages] show dd/hh:mm:ss.ms --- GPy/core/verbose_optimization.py | 45 +++++++++++++++++++++++--------- 1 file changed, 32 insertions(+), 13 deletions(-) diff --git a/GPy/core/verbose_optimization.py b/GPy/core/verbose_optimization.py index f882f228..0b1a5596 100644 --- a/GPy/core/verbose_optimization.py +++ b/GPy/core/verbose_optimization.py @@ -5,9 +5,10 @@ from __future__ import print_function import numpy as np import sys import time +import datetime def exponents(fnow, current_grad): - exps = [np.abs(np.float(fnow)), current_grad] + exps = [np.abs(np.float(fnow)), 1 if current_grad is np.nan else current_grad] return np.sign(exps) * np.log10(exps).astype(int) class VerboseOptimization(object): @@ -23,6 +24,7 @@ class VerboseOptimization(object): self.model.add_observer(self, self.print_status) self.status = 'running' self.clear = clear_after_finish + self.deltat = .2 self.update() @@ -44,25 +46,25 @@ class VerboseOptimization(object): self.hor_align = FlexBox(children = [left_col, right_col], width='100%', orientation='horizontal') display(self.hor_align) - + try: self.text.set_css('width', '100%') left_col.set_css({ 'padding': '2px', 'width': "100%", }) - + right_col.set_css({ 'padding': '2px', }) - + self.hor_align.set_css({ 'width': "100%", }) self.hor_align.remove_class('vbox') self.hor_align.add_class('hbox') - + left_col.add_class("box-flex1") right_col.add_class('box-flex0') @@ -74,16 +76,29 @@ class VerboseOptimization(object): else: self.exps = exponents(self.fnow, self.current_gradient) print('Running {} Code:'.format(self.opt_name)) - print(' {3:7s} {0:{mi}s} {1:11s} {2:11s}'.format("i", "f", "|g|", "secs", mi=self.len_maxiters)) + print(' {3:7s} {0:{mi}s} {1:11s} {2:11s}'.format("i", "f", "|g|", "runtime", mi=self.len_maxiters)) def __enter__(self): self.start = time.time() return self - def print_out(self): + def print_out(self, seconds): + if seconds<60: + self.timestring = "{:0>5.2f}".format(seconds) + else: + m, s = divmod(seconds, 60) + if m>59: + h, m = divmod(m, 60) + if h>23: + d, h = divmod(h, 24) + self.timestring = '{d:0>2d}/{h:0>2d}:{m:0>2d}'.format(m=int(m), h=int(h), d=int(d)) + else: + self.timestring = '{h:0>2d}:{m:0>2d}:{s:0>2d}'.format(m=int(m), s=int(s), h=int(h)) + else: + self.timestring = '{m:0>2d}:{s:0>5.2f}'.format(m=int(m), s=s) if self.ipython_notebook: names_vals = [['optimizer', "{:s}".format(self.opt_name)], - ['runtime [s]', "{:> g}".format(time.time()-self.start)], + ['runtime', "{:>s}".format(self.timestring)], ['evaluation', "{:>0{l}}".format(self.iteration, l=self.len_maxiters)], ['objective', "{: > 12.3E}".format(self.fnow)], ['||gradient||', "{: >+12.3E}".format(float(self.current_gradient))], @@ -120,14 +135,18 @@ class VerboseOptimization(object): if b: self.exps = n_exps print('\r', end=' ') - print('{3:> 7.2g} {0:>0{mi}g} {1:> 12e} {2:> 12e}'.format(self.iteration, float(self.fnow), float(self.current_gradient), time.time()-self.start, mi=self.len_maxiters), end=' ') # print 'Iteration:', iteration, ' Objective:', fnow, ' Scale:', beta, '\r', + print('{3:} {0:>0{mi}g} {1:> 12e} {2:> 12e}'.format(self.iteration, float(self.fnow), float(self.current_gradient), "{:>8s}".format(self.timestring), mi=self.len_maxiters), end=' ') # print 'Iteration:', iteration, ' Objective:', fnow, ' Scale:', beta, '\r', sys.stdout.flush() def print_status(self, me, which=None): self.update() + seconds = time.time()-self.start #sys.stdout.write(" "*len(self.message)) - self.print_out() + self.deltat += seconds + if self.deltat > .2: + self.print_out(seconds) + self.deltat = 0 self.iteration += 1 @@ -153,12 +172,12 @@ class VerboseOptimization(object): if self.verbose: self.stop = time.time() self.model.remove_observer(self) - self.print_out() + self.print_out(self.stop - self.start) if not self.ipython_notebook: print() - print('Optimization finished in {0:.5g} Seconds'.format(self.stop-self.start)) - print('Optimization status: {0}'.format(self.status)) + print('Runtime: {}'.format("{:>9s}".format(self.timestring))) + print('Optimization status: {0}'.format(self.status)) print() elif self.clear: self.hor_align.close() From 9ededd5a45e2bf501e1c0aa9275c2ce4f54e9888 Mon Sep 17 00:00:00 2001 From: Max Zwiessele Date: Thu, 14 May 2015 14:04:59 +0100 Subject: [PATCH 07/41] [opt messages] show DDdHHhMMmSSsMS --- GPy/core/verbose_optimization.py | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/GPy/core/verbose_optimization.py b/GPy/core/verbose_optimization.py index 0b1a5596..08c5e2dd 100644 --- a/GPy/core/verbose_optimization.py +++ b/GPy/core/verbose_optimization.py @@ -84,18 +84,20 @@ class VerboseOptimization(object): def print_out(self, seconds): if seconds<60: - self.timestring = "{:0>5.2f}".format(seconds) + ms = (seconds%1)*100 + self.timestring = "{s:0>2d}s{ms:0>2d}".format(s=int(seconds), ms=int(ms)) else: m, s = divmod(seconds, 60) if m>59: h, m = divmod(m, 60) if h>23: d, h = divmod(h, 24) - self.timestring = '{d:0>2d}/{h:0>2d}:{m:0>2d}'.format(m=int(m), h=int(h), d=int(d)) + self.timestring = '{d:0>2d}d{h:0>2d}h{m:0>2d}'.format(m=int(m), h=int(h), d=int(d)) else: - self.timestring = '{h:0>2d}:{m:0>2d}:{s:0>2d}'.format(m=int(m), s=int(s), h=int(h)) + self.timestring = '{h:0>2d}h{m:0>2d}m{s:0>2d}'.format(m=int(m), s=int(s), h=int(h)) else: - self.timestring = '{m:0>2d}:{s:0>5.2f}'.format(m=int(m), s=s) + ms = (seconds%1)*100 + self.timestring = '{m:0>2d}m{s:0>2d}s{ms:0>2d}'.format(m=int(m), s=int(s), ms=int(ms)) if self.ipython_notebook: names_vals = [['optimizer', "{:s}".format(self.opt_name)], ['runtime', "{:>s}".format(self.timestring)], From 14043be0ce46cc92868e7bee6864aab7d9051223 Mon Sep 17 00:00:00 2001 From: James Hensman Date: Thu, 14 May 2015 16:49:11 +0100 Subject: [PATCH 08/41] svgp, more c-ordering --- .../latent_function_inference/svgp.py | 35 +++++++++++++------ 1 file changed, 24 insertions(+), 11 deletions(-) diff --git a/GPy/inference/latent_function_inference/svgp.py b/GPy/inference/latent_function_inference/svgp.py index b23a09b0..b3e62118 100644 --- a/GPy/inference/latent_function_inference/svgp.py +++ b/GPy/inference/latent_function_inference/svgp.py @@ -3,6 +3,7 @@ from ...util import linalg from ...util import choleskies import numpy as np from .posterior import Posterior +from scipy.linalg.blas import dgemm class SVGP(LatentFunctionInference): @@ -37,16 +38,16 @@ class SVGP(LatentFunctionInference): #compute kernel related stuff Kmm = kern.K(Z) - Knm = kern.K(X, Z) + Kmn = kern.K(Z, X) Knn_diag = kern.Kdiag(X) Kmmi, Lm, Lmi, logdetKmm = linalg.pdinv(Kmm) #compute the marginal means and variances of q(f) - A = np.dot(Knm, Kmmi) - mu = prior_mean_f + np.dot(A, q_u_mean - prior_mean_u) - #v = Knn_diag[:,None] - np.sum(A*Knm,1)[:,None] + np.sum(A[:,:,None] * np.einsum('ij,jlk->ilk', A, S),1) - #v = Knn_diag[:,None] - np.sum(A*Knm,1)[:,None] + np.sum(A[:,:,None] * linalg.ij_jlk_to_ilk(A, S),1) - v = Knn_diag[:,None] - np.sum(A*Knm,1)[:,None] + (S.dot(A.T)*A.T[None,:,:]).sum(1).T + A = np.dot(Kmmi, Kmn) + mu = prior_mean_f + np.dot(A.T, q_u_mean - prior_mean_u) + LA = L.reshape(-1, num_inducing).dot(A).reshape(num_outputs, num_inducing, num_data) + v = (Knn_diag - np.sum(A*Kmn,0))[:,None] + np.sum(np.square(LA),1).T + #compute the KL term Kmmim = np.dot(Kmmi, q_u_mean) @@ -80,14 +81,26 @@ class SVGP(LatentFunctionInference): dF_dthetaL = dF_dthetaL.sum(1).sum(1)*batch_scale #derivatives of expected likelihood, assuming zero mean function - Adv = A.T[None,:,:]*dF_dv.T[:,None,:] # As if dF_Dv is diagonal, D, M, N - Admu = A.T.dot(dF_dmu) - AdvA = np.dot(Adv, A) # D, M, M + Adv = A[None,:,:]*dF_dv.T[:,None,:] # As if dF_Dv is diagonal, D, M, N + Admu = A.dot(dF_dmu) + #AdvA_ = np.dot(Adv, A) # D, M, M + AdvA = np.dot(Adv.reshape(-1, num_data),A.T).reshape(num_outputs, num_inducing, num_inducing ) + #assert np.allclose(AdvA, AdvA_, 1e-9) + tmp = np.sum([np.dot(a,s) for a, s in zip(AdvA, S)],0).dot(Kmmi) dF_dKmm = -Admu.dot(Kmmim.T) + AdvA.sum(0) - tmp - tmp.T dF_dKmm = 0.5*(dF_dKmm + dF_dKmm.T) # necessary? GPy bug? - tmp = 2.*(S.dot(Kmmi).swapaxes(1,2) - np.eye(num_inducing)[None, :,:]) # TODO: transpose? - dF_dKmn = np.sum([np.dot(a,b) for a,b in zip(tmp, Adv)],0) + Kmmim.dot(dF_dmu.T) + tmp = S.reshape(-1, num_inducing).dot(Kmmi).reshape(num_outputs, num_inducing , num_inducing ) + #tmp_ = S.dot(Kmmi).swapaxes(1,2) + tmp = 2.*(tmp - np.eye(num_inducing)[None, :,:]) + + #dF_dKmn_ = np.sum([np.dot(a,b) for a,b in zip(tmp, Adv)],0) + Kmmim.dot(dF_dmu.T) + dF_dKnm = Kmmim.dot(dF_dmu.T).T + assert dF_dKnm.flags['F_CONTIGUOUS'] # needed for dgemm in place call: + for a,b in zip(tmp, Adv): + dgemm(1.0, b.T, a.T, beta=1., c=dF_dKnm, overwrite_c=True) + dF_dKmn = dF_dKnm.T + dF_dm = Admu dF_dS = AdvA From 0547177f321335668f20abb2558e9351fa8e32dc Mon Sep 17 00:00:00 2001 From: Zhenwen Dai Date: Thu, 14 May 2015 17:38:07 +0100 Subject: [PATCH 09/41] change the behavior the optimize_restarts to keep the original model parameters for the firt run --- GPy/core/model.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/GPy/core/model.py b/GPy/core/model.py index 937d30e5..c3ad5cbe 100644 --- a/GPy/core/model.py +++ b/GPy/core/model.py @@ -76,7 +76,7 @@ class Model(Parameterized): jobs = [] pool = mp.Pool(processes=num_processes) for i in range(num_restarts): - self.randomize() + if i>0: self.randomize() job = pool.apply_async(opt_wrapper, args=(self,), kwds=kwargs) jobs.append(job) @@ -90,7 +90,7 @@ class Model(Parameterized): for i in range(num_restarts): try: if not parallel: - self.randomize() + if i>0: self.randomize() self.optimize(**kwargs) else: self.optimization_runs.append(jobs[i].get()) From 9750f7924514c4eded3278bd6f9ee68830f567f7 Mon Sep 17 00:00:00 2001 From: James Hensman Date: Thu, 14 May 2015 17:40:10 +0100 Subject: [PATCH 10/41] omp for gradients_X --- GPy/kern/_src/stationary_utils.c | 19 ++++++++++--------- 1 file changed, 10 insertions(+), 9 deletions(-) diff --git a/GPy/kern/_src/stationary_utils.c b/GPy/kern/_src/stationary_utils.c index abc20820..2ebeae3c 100644 --- a/GPy/kern/_src/stationary_utils.c +++ b/GPy/kern/_src/stationary_utils.c @@ -1,19 +1,20 @@ void _grad_X(int N, int D, int M, double* X, double* X2, double* tmp, double* grad){ -int n,m,d; double retnd; -//#pragma omp parallel for private(n,d, retnd, m) -for(d=0;d Date: Fri, 15 May 2015 08:10:34 +0100 Subject: [PATCH 11/41] interim svgp commit --- .../latent_function_inference/svgp.py | 19 +++++++++++-------- GPy/kern/_src/stationary_utils.c | 18 ++++++++++++++++++ 2 files changed, 29 insertions(+), 8 deletions(-) diff --git a/GPy/inference/latent_function_inference/svgp.py b/GPy/inference/latent_function_inference/svgp.py index b3e62118..2eceb154 100644 --- a/GPy/inference/latent_function_inference/svgp.py +++ b/GPy/inference/latent_function_inference/svgp.py @@ -3,7 +3,7 @@ from ...util import linalg from ...util import choleskies import numpy as np from .posterior import Posterior -from scipy.linalg.blas import dgemm +from scipy.linalg.blas import dgemm, dsymm, dtrmm class SVGP(LatentFunctionInference): @@ -46,6 +46,13 @@ class SVGP(LatentFunctionInference): A = np.dot(Kmmi, Kmn) mu = prior_mean_f + np.dot(A.T, q_u_mean - prior_mean_u) LA = L.reshape(-1, num_inducing).dot(A).reshape(num_outputs, num_inducing, num_data) + #LA = np.empty((num_outputs, num_inducing, num_data)) + #Af = np.asfortranarray(A) + #for Li, LAi in zip(L, LA): + #LAi[:,:] = dtrmm(1., Li.T, Af, side=0, lower=0, trans_a=1, overwrite_b=0) + #stop + #assert np.allclose(LA, LA_) + v = (Knn_diag - np.sum(A*Kmn,0))[:,None] + np.sum(np.square(LA),1).T @@ -83,22 +90,18 @@ class SVGP(LatentFunctionInference): #derivatives of expected likelihood, assuming zero mean function Adv = A[None,:,:]*dF_dv.T[:,None,:] # As if dF_Dv is diagonal, D, M, N Admu = A.dot(dF_dmu) - #AdvA_ = np.dot(Adv, A) # D, M, M + Adv = np.ascontiguousarray(Adv) # makes for faster operations later... AdvA = np.dot(Adv.reshape(-1, num_data),A.T).reshape(num_outputs, num_inducing, num_inducing ) - #assert np.allclose(AdvA, AdvA_, 1e-9) - tmp = np.sum([np.dot(a,s) for a, s in zip(AdvA, S)],0).dot(Kmmi) dF_dKmm = -Admu.dot(Kmmim.T) + AdvA.sum(0) - tmp - tmp.T dF_dKmm = 0.5*(dF_dKmm + dF_dKmm.T) # necessary? GPy bug? tmp = S.reshape(-1, num_inducing).dot(Kmmi).reshape(num_outputs, num_inducing , num_inducing ) - #tmp_ = S.dot(Kmmi).swapaxes(1,2) tmp = 2.*(tmp - np.eye(num_inducing)[None, :,:]) - #dF_dKmn_ = np.sum([np.dot(a,b) for a,b in zip(tmp, Adv)],0) + Kmmim.dot(dF_dmu.T) dF_dKnm = Kmmim.dot(dF_dmu.T).T - assert dF_dKnm.flags['F_CONTIGUOUS'] # needed for dgemm in place call: + assert dF_dKnm.flags['F_CONTIGUOUS'] # needed for dsymm in place call: for a,b in zip(tmp, Adv): - dgemm(1.0, b.T, a.T, beta=1., c=dF_dKnm, overwrite_c=True) + dsymm(1.0, a.T, b.T, beta=1., side=1, c=dF_dKnm, overwrite_c=True) dF_dKmn = dF_dKnm.T dF_dm = Admu diff --git a/GPy/kern/_src/stationary_utils.c b/GPy/kern/_src/stationary_utils.c index 2ebeae3c..1ae1ff33 100644 --- a/GPy/kern/_src/stationary_utils.c +++ b/GPy/kern/_src/stationary_utils.c @@ -14,6 +14,22 @@ for(nd=0;nd<(D*N);nd++){ } //grad_X +void _lengthscale_grads_unsafe(int N, int M, int Q, double* tmp, double* X, double* X2, double* grad){ +int n,m,nm,q,nQ,mQ; +double dist; +#pragma omp parallel for private(n,m,nm,q,nQ,mQ,dist) +for(nm=0; nm<(N*M); nm++){ + n = nm/M; + m = nm%M; + nQ = n*Q; + mQ = m*Q; + for(q=0; q Date: Fri, 15 May 2015 08:59:19 +0100 Subject: [PATCH 12/41] svgp working with reordered chols --- .../latent_function_inference/svgp.py | 20 ++---- GPy/util/choleskies.py | 10 +-- GPy/util/choleskies_cython.c | 68 +++++++++---------- GPy/util/choleskies_cython.pyx | 12 ++-- 4 files changed, 51 insertions(+), 59 deletions(-) diff --git a/GPy/inference/latent_function_inference/svgp.py b/GPy/inference/latent_function_inference/svgp.py index 2eceb154..3c4602cc 100644 --- a/GPy/inference/latent_function_inference/svgp.py +++ b/GPy/inference/latent_function_inference/svgp.py @@ -24,8 +24,6 @@ class SVGP(LatentFunctionInference): if np.any(np.isinf(Si)): raise ValueError("Cholesky representation unstable") - #S = S + np.eye(S.shape[0])*1e-5*np.max(np.max(S)) - #Si, Lnew, _,_ = linalg.pdinv(S) #compute mean function stuff if mean_function is not None: @@ -35,27 +33,21 @@ class SVGP(LatentFunctionInference): prior_mean_u = np.zeros((num_inducing, num_outputs)) prior_mean_f = np.zeros((num_data, num_outputs)) - #compute kernel related stuff Kmm = kern.K(Z) Kmn = kern.K(Z, X) Knn_diag = kern.Kdiag(X) - Kmmi, Lm, Lmi, logdetKmm = linalg.pdinv(Kmm) + Lm = linalg.jitchol(Kmm) + logdetKmm = 2.*np.sum(np.log(np.diag(Lm))) + Kmmi, _ = linalg.dpotri(Lm) #compute the marginal means and variances of q(f) - A = np.dot(Kmmi, Kmn) + A, _ = linalg.dpotrs(Lm, Kmn) mu = prior_mean_f + np.dot(A.T, q_u_mean - prior_mean_u) LA = L.reshape(-1, num_inducing).dot(A).reshape(num_outputs, num_inducing, num_data) - #LA = np.empty((num_outputs, num_inducing, num_data)) - #Af = np.asfortranarray(A) - #for Li, LAi in zip(L, LA): - #LAi[:,:] = dtrmm(1., Li.T, Af, side=0, lower=0, trans_a=1, overwrite_b=0) - #stop - #assert np.allclose(LA, LA_) - + #TODO? possibly use dtrmm for the above line? v = (Knn_diag - np.sum(A*Kmn,0))[:,None] + np.sum(np.square(LA),1).T - #compute the KL term Kmmim = np.dot(Kmmi, q_u_mean) KLs = -0.5*logdetS -0.5*num_inducing + 0.5*logdetKmm + 0.5*np.sum(Kmmi[None,:,:]*S,1).sum(1) + 0.5*np.sum(q_u_mean*Kmmim,0) @@ -90,7 +82,7 @@ class SVGP(LatentFunctionInference): #derivatives of expected likelihood, assuming zero mean function Adv = A[None,:,:]*dF_dv.T[:,None,:] # As if dF_Dv is diagonal, D, M, N Admu = A.dot(dF_dmu) - Adv = np.ascontiguousarray(Adv) # makes for faster operations later... + Adv = np.ascontiguousarray(Adv) # makes for faster operations later...(inc dsymm) AdvA = np.dot(Adv.reshape(-1, num_data),A.T).reshape(num_outputs, num_inducing, num_inducing ) tmp = np.sum([np.dot(a,s) for a, s in zip(AdvA, S)],0).dot(Kmmi) dF_dKmm = -Admu.dot(Kmmim.T) + AdvA.sum(0) - tmp - tmp.T diff --git a/GPy/util/choleskies.py b/GPy/util/choleskies.py index e9731f38..7afc3098 100644 --- a/GPy/util/choleskies.py +++ b/GPy/util/choleskies.py @@ -15,19 +15,19 @@ def safe_root(N): return j def _flat_to_triang_pure(flat_mat): - D, N = flat_mat.shape + N, D = flat_mat.shape M = (-1 + safe_root(8*N+1))//2 ret = np.zeros((D, M, M)) for d in range(D): count = 0 for m in range(M): for mm in range(m+1): - ret[d,m, mm] = flat_mat[d, count]; + ret[d,m, mm] = flat_mat[count, d]; count = count+1 return ret def _flat_to_triang_cython(flat_mat): - D, N = flat_mat.shape + N, D = flat_mat.shape M = (-1 + safe_root(8*N+1))//2 return choleskies_cython.flat_to_triang(flat_mat, M) @@ -36,12 +36,12 @@ def _triang_to_flat_pure(L): D, _, M = L.shape N = M*(M+1)//2 - flat = np.empty((D, N)) + flat = np.empty((N, D)) for d in range(D): count = 0; for m in range(M): for mm in range(m+1): - flat[d,count] = L[d, m, mm] + flat[count,d] = L[d, m, mm] count = count +1 return flat diff --git a/GPy/util/choleskies_cython.c b/GPy/util/choleskies_cython.c index d79bdbd1..069fb478 100644 --- a/GPy/util/choleskies_cython.c +++ b/GPy/util/choleskies_cython.c @@ -1167,13 +1167,13 @@ static PyObject *__pyx_codeobj__12; * cimport numpy as np * * def flat_to_triang(np.ndarray[double, ndim=2] flat, int M): # <<<<<<<<<<<<<< - * """take a matrix D x N and return a D X M x M array where + * """take a matrix N x D and return a D X M x M array where * */ /* Python wrapper */ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_1flat_to_triang(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -static char __pyx_doc_3GPy_4util_17choleskies_cython_flat_to_triang[] = "take a matrix D x N and return a D X M x M array where\n\n N = M(M+1)/2\n\n the lower triangluar portion of the d'th slice of the result is filled by the d'th column of flat.\n "; +static char __pyx_doc_3GPy_4util_17choleskies_cython_flat_to_triang[] = "take a matrix N x D and return a D X M x M array where\n\n N = M(M+1)/2\n\n the lower triangluar portion of the d'th slice of the result is filled by the d'th column of flat.\n "; static PyMethodDef __pyx_mdef_3GPy_4util_17choleskies_cython_1flat_to_triang = {"flat_to_triang", (PyCFunction)__pyx_pw_3GPy_4util_17choleskies_cython_1flat_to_triang, METH_VARARGS|METH_KEYWORDS, __pyx_doc_3GPy_4util_17choleskies_cython_flat_to_triang}; static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_1flat_to_triang(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { PyArrayObject *__pyx_v_flat = 0; @@ -1292,24 +1292,24 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U /* "GPy/util/choleskies_cython.pyx":17 * the lower triangluar portion of the d'th slice of the result is filled by the d'th column of flat. * """ - * cdef int D = flat.shape[0] # <<<<<<<<<<<<<< - * cdef int N = flat.shape[1] + * cdef int D = flat.shape[1] # <<<<<<<<<<<<<< + * cdef int N = flat.shape[0] * cdef int count = 0 */ - __pyx_v_D = (__pyx_v_flat->dimensions[0]); + __pyx_v_D = (__pyx_v_flat->dimensions[1]); /* "GPy/util/choleskies_cython.pyx":18 * """ - * cdef int D = flat.shape[0] - * cdef int N = flat.shape[1] # <<<<<<<<<<<<<< + * cdef int D = flat.shape[1] + * cdef int N = flat.shape[0] # <<<<<<<<<<<<<< * cdef int count = 0 * cdef np.ndarray[double, ndim=3] ret = np.zeros((D, M, M)) */ - __pyx_v_N = (__pyx_v_flat->dimensions[1]); + __pyx_v_N = (__pyx_v_flat->dimensions[0]); /* "GPy/util/choleskies_cython.pyx":19 - * cdef int D = flat.shape[0] - * cdef int N = flat.shape[1] + * cdef int D = flat.shape[1] + * cdef int N = flat.shape[0] * cdef int count = 0 # <<<<<<<<<<<<<< * cdef np.ndarray[double, ndim=3] ret = np.zeros((D, M, M)) * cdef int d, m, mm @@ -1317,7 +1317,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U __pyx_v_count = 0; /* "GPy/util/choleskies_cython.pyx":20 - * cdef int N = flat.shape[1] + * cdef int N = flat.shape[0] * cdef int count = 0 * cdef np.ndarray[double, ndim=3] ret = np.zeros((D, M, M)) # <<<<<<<<<<<<<< * cdef int d, m, mm @@ -1410,7 +1410,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U * count = 0 * for m in range(M): # <<<<<<<<<<<<<< * for mm in range(m+1): - * ret[d, m, mm] = flat[d,count] + * ret[d, m, mm] = flat[count,d] */ __pyx_t_10 = __pyx_v_M; for (__pyx_t_11 = 0; __pyx_t_11 < __pyx_t_10; __pyx_t_11+=1) { @@ -1420,7 +1420,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U * count = 0 * for m in range(M): * for mm in range(m+1): # <<<<<<<<<<<<<< - * ret[d, m, mm] = flat[d,count] + * ret[d, m, mm] = flat[count,d] * count += 1 */ __pyx_t_12 = (__pyx_v_m + 1); @@ -1430,12 +1430,12 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U /* "GPy/util/choleskies_cython.pyx":26 * for m in range(M): * for mm in range(m+1): - * ret[d, m, mm] = flat[d,count] # <<<<<<<<<<<<<< + * ret[d, m, mm] = flat[count,d] # <<<<<<<<<<<<<< * count += 1 * return ret */ - __pyx_t_14 = __pyx_v_d; - __pyx_t_15 = __pyx_v_count; + __pyx_t_14 = __pyx_v_count; + __pyx_t_15 = __pyx_v_d; if (__pyx_t_14 < 0) __pyx_t_14 += __pyx_pybuffernd_flat.diminfo[0].shape; if (__pyx_t_15 < 0) __pyx_t_15 += __pyx_pybuffernd_flat.diminfo[1].shape; __pyx_t_16 = __pyx_v_d; @@ -1448,7 +1448,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U /* "GPy/util/choleskies_cython.pyx":27 * for mm in range(m+1): - * ret[d, m, mm] = flat[d,count] + * ret[d, m, mm] = flat[count,d] * count += 1 # <<<<<<<<<<<<<< * return ret * @@ -1459,7 +1459,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U } /* "GPy/util/choleskies_cython.pyx":28 - * ret[d, m, mm] = flat[d,count] + * ret[d, m, mm] = flat[count,d] * count += 1 * return ret # <<<<<<<<<<<<<< * @@ -1474,7 +1474,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U * cimport numpy as np * * def flat_to_triang(np.ndarray[double, ndim=2] flat, int M): # <<<<<<<<<<<<<< - * """take a matrix D x N and return a D X M x M array where + * """take a matrix N x D and return a D X M x M array where * */ @@ -1607,7 +1607,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ * cdef int M = L.shape[1] * cdef int N = M*(M+1)/2 # <<<<<<<<<<<<<< * cdef int count = 0 - * cdef np.ndarray[double, ndim=2] flat = np.empty((D, N)) + * cdef np.ndarray[double, ndim=2] flat = np.empty((N, D)) */ __pyx_v_N = __Pyx_div_long((__pyx_v_M * (__pyx_v_M + 1)), 2); @@ -1615,7 +1615,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ * cdef int M = L.shape[1] * cdef int N = M*(M+1)/2 * cdef int count = 0 # <<<<<<<<<<<<<< - * cdef np.ndarray[double, ndim=2] flat = np.empty((D, N)) + * cdef np.ndarray[double, ndim=2] flat = np.empty((N, D)) * cdef int d, m, mm */ __pyx_v_count = 0; @@ -1623,7 +1623,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ /* "GPy/util/choleskies_cython.pyx":35 * cdef int N = M*(M+1)/2 * cdef int count = 0 - * cdef np.ndarray[double, ndim=2] flat = np.empty((D, N)) # <<<<<<<<<<<<<< + * cdef np.ndarray[double, ndim=2] flat = np.empty((N, D)) # <<<<<<<<<<<<<< * cdef int d, m, mm * for d in range(D): */ @@ -1632,9 +1632,9 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ __pyx_t_3 = __Pyx_PyObject_GetAttrStr(__pyx_t_2, __pyx_n_s_empty); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 35; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - __pyx_t_2 = __Pyx_PyInt_From_int(__pyx_v_D); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 35; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = __Pyx_PyInt_From_int(__pyx_v_N); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 35; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); - __pyx_t_4 = __Pyx_PyInt_From_int(__pyx_v_N); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 35; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_int(__pyx_v_D); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 35; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __pyx_t_5 = PyTuple_New(2); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 35; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); @@ -1685,7 +1685,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ __pyx_t_1 = 0; /* "GPy/util/choleskies_cython.pyx":37 - * cdef np.ndarray[double, ndim=2] flat = np.empty((D, N)) + * cdef np.ndarray[double, ndim=2] flat = np.empty((N, D)) * cdef int d, m, mm * for d in range(D): # <<<<<<<<<<<<<< * count = 0 @@ -1709,7 +1709,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ * count = 0 * for m in range(M): # <<<<<<<<<<<<<< * for mm in range(m+1): - * flat[d,count] = L[d, m, mm] + * flat[count,d] = L[d, m, mm] */ __pyx_t_9 = __pyx_v_M; for (__pyx_t_10 = 0; __pyx_t_10 < __pyx_t_9; __pyx_t_10+=1) { @@ -1719,7 +1719,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ * count = 0 * for m in range(M): * for mm in range(m+1): # <<<<<<<<<<<<<< - * flat[d,count] = L[d, m, mm] + * flat[count,d] = L[d, m, mm] * count += 1 */ __pyx_t_11 = (__pyx_v_m + 1); @@ -1729,7 +1729,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ /* "GPy/util/choleskies_cython.pyx":41 * for m in range(M): * for mm in range(m+1): - * flat[d,count] = L[d, m, mm] # <<<<<<<<<<<<<< + * flat[count,d] = L[d, m, mm] # <<<<<<<<<<<<<< * count += 1 * return flat */ @@ -1739,15 +1739,15 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ if (__pyx_t_13 < 0) __pyx_t_13 += __pyx_pybuffernd_L.diminfo[0].shape; if (__pyx_t_14 < 0) __pyx_t_14 += __pyx_pybuffernd_L.diminfo[1].shape; if (__pyx_t_15 < 0) __pyx_t_15 += __pyx_pybuffernd_L.diminfo[2].shape; - __pyx_t_16 = __pyx_v_d; - __pyx_t_17 = __pyx_v_count; + __pyx_t_16 = __pyx_v_count; + __pyx_t_17 = __pyx_v_d; if (__pyx_t_16 < 0) __pyx_t_16 += __pyx_pybuffernd_flat.diminfo[0].shape; if (__pyx_t_17 < 0) __pyx_t_17 += __pyx_pybuffernd_flat.diminfo[1].shape; *__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_flat.rcbuffer->pybuffer.buf, __pyx_t_16, __pyx_pybuffernd_flat.diminfo[0].strides, __pyx_t_17, __pyx_pybuffernd_flat.diminfo[1].strides) = (*__Pyx_BufPtrStrided3d(double *, __pyx_pybuffernd_L.rcbuffer->pybuffer.buf, __pyx_t_13, __pyx_pybuffernd_L.diminfo[0].strides, __pyx_t_14, __pyx_pybuffernd_L.diminfo[1].strides, __pyx_t_15, __pyx_pybuffernd_L.diminfo[2].strides)); /* "GPy/util/choleskies_cython.pyx":42 * for mm in range(m+1): - * flat[d,count] = L[d, m, mm] + * flat[count,d] = L[d, m, mm] * count += 1 # <<<<<<<<<<<<<< * return flat * @@ -1758,7 +1758,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ } /* "GPy/util/choleskies_cython.pyx":43 - * flat[d,count] = L[d, m, mm] + * flat[count,d] = L[d, m, mm] * count += 1 * return flat # <<<<<<<<<<<<<< * @@ -4381,7 +4381,7 @@ static int __Pyx_InitCachedConstants(void) { * cimport numpy as np * * def flat_to_triang(np.ndarray[double, ndim=2] flat, int M): # <<<<<<<<<<<<<< - * """take a matrix D x N and return a D X M x M array where + * """take a matrix N x D and return a D X M x M array where * */ __pyx_tuple__7 = PyTuple_Pack(9, __pyx_n_s_flat, __pyx_n_s_M, __pyx_n_s_D, __pyx_n_s_N, __pyx_n_s_count, __pyx_n_s_ret, __pyx_n_s_d, __pyx_n_s_m, __pyx_n_s_mm); if (unlikely(!__pyx_tuple__7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 10; __pyx_clineno = __LINE__; goto __pyx_L1_error;} @@ -4539,7 +4539,7 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void) * cimport numpy as np * * def flat_to_triang(np.ndarray[double, ndim=2] flat, int M): # <<<<<<<<<<<<<< - * """take a matrix D x N and return a D X M x M array where + * """take a matrix N x D and return a D X M x M array where * */ __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_17choleskies_cython_1flat_to_triang, NULL, __pyx_n_s_GPy_util_choleskies_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 10; __pyx_clineno = __LINE__; goto __pyx_L1_error;} diff --git a/GPy/util/choleskies_cython.pyx b/GPy/util/choleskies_cython.pyx index 13f8c8ae..76b49b22 100644 --- a/GPy/util/choleskies_cython.pyx +++ b/GPy/util/choleskies_cython.pyx @@ -8,14 +8,14 @@ import numpy as np cimport numpy as np def flat_to_triang(np.ndarray[double, ndim=2] flat, int M): - """take a matrix D x N and return a D X M x M array where + """take a matrix N x D and return a D X M x M array where N = M(M+1)/2 the lower triangluar portion of the d'th slice of the result is filled by the d'th column of flat. """ - cdef int D = flat.shape[0] - cdef int N = flat.shape[1] + cdef int D = flat.shape[1] + cdef int N = flat.shape[0] cdef int count = 0 cdef np.ndarray[double, ndim=3] ret = np.zeros((D, M, M)) cdef int d, m, mm @@ -23,7 +23,7 @@ def flat_to_triang(np.ndarray[double, ndim=2] flat, int M): count = 0 for m in range(M): for mm in range(m+1): - ret[d, m, mm] = flat[d,count] + ret[d, m, mm] = flat[count,d] count += 1 return ret @@ -32,13 +32,13 @@ def triang_to_flat(np.ndarray[double, ndim=3] L): cdef int M = L.shape[1] cdef int N = M*(M+1)/2 cdef int count = 0 - cdef np.ndarray[double, ndim=2] flat = np.empty((D, N)) + cdef np.ndarray[double, ndim=2] flat = np.empty((N, D)) cdef int d, m, mm for d in range(D): count = 0 for m in range(M): for mm in range(m+1): - flat[d,count] = L[d, m, mm] + flat[count,d] = L[d, m, mm] count += 1 return flat From 51a4e881da3be605894077c0904aa82d2166e25d Mon Sep 17 00:00:00 2001 From: James Hensman Date: Fri, 15 May 2015 09:02:48 +0100 Subject: [PATCH 13/41] small bug in cython tests --- GPy/testing/cython_tests.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/testing/cython_tests.py b/GPy/testing/cython_tests.py index 6c8c4c0f..f88f12f3 100644 --- a/GPy/testing/cython_tests.py +++ b/GPy/testing/cython_tests.py @@ -9,7 +9,7 @@ These tests make sure that the opure python and cython codes work the same class CythonTestChols(np.testing.TestCase): def setUp(self): - self.flat = np.random.randn(5,45) + self.flat = np.random.randn(45,5) self.triang = np.array([np.eye(20) for i in range(3)]) def test_flat_to_triang(self): L1 = choleskies._flat_to_triang_pure(self.flat) From d01545c92b8cbd9995fc32d35b878a8f61a67b39 Mon Sep 17 00:00:00 2001 From: Zhenwen Dai Date: Sat, 16 May 2015 22:39:11 +0100 Subject: [PATCH 14/41] prevent the predicted variance to be negative --- GPy/core/gp.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index c2d2010c..63316384 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -209,6 +209,8 @@ class GP(Model): var = Kxx - np.sum(WiKx*Kx, 0) var = var.reshape(-1, 1) + var[var<0.] = 0. + #force mu to be a column vector if len(mu.shape)==1: mu = mu[:,None] From 7188e92efb2b57996fea068fadcc4782954095a3 Mon Sep 17 00:00:00 2001 From: Zhenwen Dai Date: Mon, 18 May 2015 16:36:39 +0100 Subject: [PATCH 15/41] start implement ICP for ssgplvm --- GPy/core/parameterization/variational.py | 6 +- GPy/examples/dimensionality_reduction.py | 2 +- GPy/models/ss_gplvm.py | 82 +++++++++++++++++++++++- 3 files changed, 84 insertions(+), 6 deletions(-) diff --git a/GPy/core/parameterization/variational.py b/GPy/core/parameterization/variational.py index ab196b98..09191c0b 100644 --- a/GPy/core/parameterization/variational.py +++ b/GPy/core/parameterization/variational.py @@ -179,15 +179,15 @@ class SpikeAndSlabPosterior(VariationalPosterior): n.parameters[dc['variance']._parent_index_] = dc['variance'] n.parameters[dc['binary_prob']._parent_index_] = dc['binary_prob'] n._gradient_array_ = None - oversize = self.size - self.mean.size - self.variance.size - n.size = n.mean.size + n.variance.size + oversize + oversize = self.size - self.mean.size - self.variance.size - self.gamma.size + n.size = n.mean.size + n.variance.size + n.gamma.size + oversize n.ndim = n.mean.ndim n.shape = n.mean.shape n.num_data = n.mean.shape[0] n.input_dim = n.mean.shape[1] if n.ndim != 1 else 1 return n else: - return super(VariationalPrior, self).__getitem__(s) + return super(SpikeAndSlabPosterior, self).__getitem__(s) def plot(self, *args, **kwargs): """ diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py index 46107a71..37870581 100644 --- a/GPy/examples/dimensionality_reduction.py +++ b/GPy/examples/dimensionality_reduction.py @@ -359,7 +359,7 @@ def ssgplvm_simulation(optimize=True, verbose=1, if optimize: print("Optimizing model:") - m.optimize('scg', messages=verbose, max_iters=max_iters, + m.optimize('bfgs', messages=verbose, max_iters=max_iters, gtol=.05) if plot: m.X.plot("SSGPLVM Latent Space 1D") diff --git a/GPy/models/ss_gplvm.py b/GPy/models/ss_gplvm.py index 0f3b8fdd..44eea74c 100644 --- a/GPy/models/ss_gplvm.py +++ b/GPy/models/ss_gplvm.py @@ -5,11 +5,91 @@ import numpy as np from ..core.sparse_gp_mpi import SparseGP_MPI from .. import kern +from ..core.parameterization import Param from ..likelihoods import Gaussian from ..core.parameterization.variational import SpikeAndSlabPrior, SpikeAndSlabPosterior from ..inference.latent_function_inference.var_dtc_parallel import update_gradients, VarDTC_minibatch from ..kern._src.psi_comp.ssrbf_psi_gpucomp import PSICOMP_SSRBF_GPU +class IBPPosterior(SpikeAndSlabPosterior): + ''' + The SpikeAndSlab distribution for variational approximations. + ''' + def __init__(self, means, variances, binary_prob, tau, name='latent space'): + """ + binary_prob : the probability of the distribution on the slab part. + """ + from ..core.parameterization.transformations import Logexp, __fixed__ + super(IBPPosterior, self).__init__(means, variances, name) + self.tau = Param("tau",SpikeAndSlabPosterior, Logexp) + self.link_parameter(self.tau) + + def set_gradients(self, grad): + self.mean.gradient, self.variance.gradient, self.gamma.gradient, self.tau.gradient = grad + + def __getitem__(self, s): + if isinstance(s, (int, slice, tuple, list, np.ndarray)): + import copy + n = self.__new__(self.__class__, self.name) + dc = self.__dict__.copy() + dc['mean'] = self.mean[s] + dc['variance'] = self.variance[s] + dc['binary_prob'] = self.binary_prob[s] + dc['tau'] = self.tau[s] + dc['parameters'] = copy.copy(self.parameters) + n.__dict__.update(dc) + n.parameters[dc['mean']._parent_index_] = dc['mean'] + n.parameters[dc['variance']._parent_index_] = dc['variance'] + n.parameters[dc['binary_prob']._parent_index_] = dc['binary_prob'] + n.parameters[dc['tau']._parent_index_] = dc['tau'] + n._gradient_array_ = None + oversize = self.size - self.mean.size - self.variance.size - self.gamma.size - self.tau.size + n.size = n.mean.size + n.variance.size + n.gamma.size+ n.tau.size + oversize + n.ndim = n.mean.ndim + n.shape = n.mean.shape + n.num_data = n.mean.shape[0] + n.input_dim = n.mean.shape[1] if n.ndim != 1 else 1 + return n + else: + return super(IBPPosterior, self).__getitem__(s) + +class IBPPrior(SpikeAndSlabPrior): + def __init__(self, input_dim, alpha =2., name='IBPPrior', **kw): + super(SpikeAndSlabPrior, self).__init__(name=name, **kw) + from ..core.parameterization.transformations import Logexp, __fixed__ + self.input_dim = input_dim + self.alpha = Param('alpha', alpha, __fixed__) + self.link_parameter(self.alpha) + + def KL_divergence(self, variational_posterior): + mu, S, gamma, tau = variational_posterior.mean.values, variational_posterior.variance.values, variational_posterior.gamma.values, variational_posterior.tau.values + + var_mean = np.square(mu)/self.variance + var_S = (S/self.variance - np.log(S)) + part1 = (gamma* (np.log(self.variance)-1. +var_mean + var_S)).sum()/2. + + ad = self.alpha/self.input_dim + from scipy.special import betaln,digamma + part2 = (gamma*np.log(gamma)).sum() + ((1.-gamma)*np.log(1.-gamma)).sum() + betaln(ad,1.)*self.input_dim \ + -betaln(tau[:,0], tau[:,1]).sum() + ((tau[:,0]-gamma-ad)*digamma(tau[:,0])).sum() + \ + ((tau[:,1]+gamma-2.)*digamma(tau[:,1])).sum() + ((2.+ad-tau[:,0]-tau[:,1])*digamma(tau.sum(axis=1))).sum() + + return part1+part2 + + def update_gradients_KL(self, variational_posterior): + mu, S, gamma, tau = variational_posterior.mean.values, variational_posterior.variance.values, variational_posterior.gamma.values, variational_posterior.tau.values + + variational_posterior.binary_prob.gradient -= ((np.square(mu)+S)/self.variance-np.log(S)+np.log(self.variance)-1.)/2. + mu.gradient -= gamma*mu/self.variance + S.gradient -= (1./self.variance - 1./S) * gamma /2. + if self.learnPi: + if len(self.pi)==1: + self.pi.gradient = (gamma/self.pi - (1.-gamma)/(1.-self.pi)).sum() + elif len(self.pi.shape)==1: + self.pi.gradient = (gamma/self.pi - (1.-gamma)/(1.-self.pi)).sum(axis=0) + else: + self.pi[idx].gradient = (gamma/self.pi[idx] - (1.-gamma)/(1.-self.pi[idx])) + class SSGPLVM(SparseGP_MPI): """ Spike-and-Slab Gaussian Process Latent Variable Model @@ -69,8 +149,6 @@ class SSGPLVM(SparseGP_MPI): X = SpikeAndSlabPosterior(X, X_variance, gamma) super(SSGPLVM,self).__init__(X, Y, Z, kernel, likelihood, variational_prior=self.variational_prior, inference_method=inference_method, name=name, mpi_comm=mpi_comm, normalizer=normalizer, **kwargs) -# self.X.unfix() -# self.X.variance.constrain_positive() self.link_parameter(self.X, index=0) if self.group_spike: From 601efa7525583632936610dd127ce870a104aa70 Mon Sep 17 00:00:00 2001 From: James Hensman Date: Tue, 19 May 2015 13:33:47 +0100 Subject: [PATCH 16/41] svgp bugfix --- GPy/inference/latent_function_inference/svgp.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/GPy/inference/latent_function_inference/svgp.py b/GPy/inference/latent_function_inference/svgp.py index 3c4602cc..b04ca609 100644 --- a/GPy/inference/latent_function_inference/svgp.py +++ b/GPy/inference/latent_function_inference/svgp.py @@ -44,9 +44,11 @@ class SVGP(LatentFunctionInference): #compute the marginal means and variances of q(f) A, _ = linalg.dpotrs(Lm, Kmn) mu = prior_mean_f + np.dot(A.T, q_u_mean - prior_mean_u) - LA = L.reshape(-1, num_inducing).dot(A).reshape(num_outputs, num_inducing, num_data) - #TODO? possibly use dtrmm for the above line? - v = (Knn_diag - np.sum(A*Kmn,0))[:,None] + np.sum(np.square(LA),1).T + v = np.empty((num_data, num_outputs)) + for i in range(num_outputs): + tmp = dtrmm(1.0,L[i].T, A, lower=0, trans_a=0) + v[:,i] = np.sum(np.square(tmp),0) + v += (Knn_diag - np.sum(A*Kmn,0))[:,None] #compute the KL term Kmmim = np.dot(Kmmi, q_u_mean) @@ -90,11 +92,9 @@ class SVGP(LatentFunctionInference): tmp = S.reshape(-1, num_inducing).dot(Kmmi).reshape(num_outputs, num_inducing , num_inducing ) tmp = 2.*(tmp - np.eye(num_inducing)[None, :,:]) - dF_dKnm = Kmmim.dot(dF_dmu.T).T - assert dF_dKnm.flags['F_CONTIGUOUS'] # needed for dsymm in place call: + dF_dKmn = Kmmim.dot(dF_dmu.T) for a,b in zip(tmp, Adv): - dsymm(1.0, a.T, b.T, beta=1., side=1, c=dF_dKnm, overwrite_c=True) - dF_dKmn = dF_dKnm.T + dF_dKmn += np.dot(a.T, b) dF_dm = Admu dF_dS = AdvA From 406b8de9a2b4166bfe3cfc16c13e77eae71afb9c Mon Sep 17 00:00:00 2001 From: James Hensman Date: Tue, 19 May 2015 16:54:02 +0100 Subject: [PATCH 17/41] some cython improvments for stationary kerns --- GPy/kern/_src/stationary_cython.c | 14772 +++++++++++++++++++++++++- GPy/kern/_src/stationary_cython.pyx | 25 +- 2 files changed, 14475 insertions(+), 322 deletions(-) diff --git a/GPy/kern/_src/stationary_cython.c b/GPy/kern/_src/stationary_cython.c index 8689150e..36a782a9 100644 --- a/GPy/kern/_src/stationary_cython.c +++ b/GPy/kern/_src/stationary_cython.c @@ -232,6 +232,8 @@ void __Pyx_call_destructor(T* x) { #include "numpy/arrayobject.h" #include "numpy/ufuncobject.h" #include "stationary_utils.h" +#include "pythread.h" +#include "pystate.h" #ifdef _OPENMP #include #endif /* _OPENMP */ @@ -437,6 +439,7 @@ static const char *__pyx_filename; static const char *__pyx_f[] = { "GPy/kern/_src/stationary_cython.pyx", "__init__.pxd", + "GPy/kern/_src/stringsource", "type.pxd", }; #define IS_UNSIGNED(type) (((type) -1) > 0) @@ -474,8 +477,64 @@ typedef struct { char is_valid_array; } __Pyx_BufFmt_Context; +struct __pyx_memoryview_obj; +typedef struct { + struct __pyx_memoryview_obj *memview; + char *data; + Py_ssize_t shape[8]; + Py_ssize_t strides[8]; + Py_ssize_t suboffsets[8]; +} __Pyx_memviewslice; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":723 +#include +#ifndef CYTHON_ATOMICS + #define CYTHON_ATOMICS 1 +#endif +#define __pyx_atomic_int_type int +#if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 || \ + (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) && \ + !defined(__i386__) + #define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1) + #define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1) + #ifdef __PYX_DEBUG_ATOMICS + #warning "Using GNU atomics" + #endif +#elif CYTHON_ATOMICS && MSC_VER + #include + #define __pyx_atomic_int_type LONG + #define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value) + #define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value) + #ifdef __PYX_DEBUG_ATOMICS + #warning "Using MSVC atomics" + #endif +#elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0 + #define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value) + #define __pyx_atomic_decr_aligned(value, lock) _InterlockedDecrement(value) + #ifdef __PYX_DEBUG_ATOMICS + #warning "Using Intel atomics" + #endif +#else + #undef CYTHON_ATOMICS + #define CYTHON_ATOMICS 0 + #ifdef __PYX_DEBUG_ATOMICS + #warning "Not using atomics" + #endif +#endif +typedef volatile __pyx_atomic_int_type __pyx_atomic_int; +#if CYTHON_ATOMICS + #define __pyx_add_acquisition_count(memview) \ + __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) + #define __pyx_sub_acquisition_count(memview) \ + __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) +#else + #define __pyx_add_acquisition_count(memview) \ + __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) + #define __pyx_sub_acquisition_count(memview) \ + __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) +#endif + + +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":723 * # in Cython to enable them only on the right systems. * * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< @@ -484,7 +543,7 @@ typedef struct { */ typedef npy_int8 __pyx_t_5numpy_int8_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":724 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":724 * * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< @@ -493,7 +552,7 @@ typedef npy_int8 __pyx_t_5numpy_int8_t; */ typedef npy_int16 __pyx_t_5numpy_int16_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":725 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":725 * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< @@ -502,7 +561,7 @@ typedef npy_int16 __pyx_t_5numpy_int16_t; */ typedef npy_int32 __pyx_t_5numpy_int32_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":726 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":726 * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< @@ -511,7 +570,7 @@ typedef npy_int32 __pyx_t_5numpy_int32_t; */ typedef npy_int64 __pyx_t_5numpy_int64_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":730 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":730 * #ctypedef npy_int128 int128_t * * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< @@ -520,7 +579,7 @@ typedef npy_int64 __pyx_t_5numpy_int64_t; */ typedef npy_uint8 __pyx_t_5numpy_uint8_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":731 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":731 * * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< @@ -529,7 +588,7 @@ typedef npy_uint8 __pyx_t_5numpy_uint8_t; */ typedef npy_uint16 __pyx_t_5numpy_uint16_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":732 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":732 * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< @@ -538,7 +597,7 @@ typedef npy_uint16 __pyx_t_5numpy_uint16_t; */ typedef npy_uint32 __pyx_t_5numpy_uint32_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":733 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":733 * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< @@ -547,7 +606,7 @@ typedef npy_uint32 __pyx_t_5numpy_uint32_t; */ typedef npy_uint64 __pyx_t_5numpy_uint64_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":737 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":737 * #ctypedef npy_uint128 uint128_t * * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< @@ -556,7 +615,7 @@ typedef npy_uint64 __pyx_t_5numpy_uint64_t; */ typedef npy_float32 __pyx_t_5numpy_float32_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":738 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":738 * * ctypedef npy_float32 float32_t * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< @@ -565,7 +624,7 @@ typedef npy_float32 __pyx_t_5numpy_float32_t; */ typedef npy_float64 __pyx_t_5numpy_float64_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":747 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":747 * # The int types are mapped a bit surprising -- * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t # <<<<<<<<<<<<<< @@ -574,7 +633,7 @@ typedef npy_float64 __pyx_t_5numpy_float64_t; */ typedef npy_long __pyx_t_5numpy_int_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":748 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":748 * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< @@ -583,7 +642,7 @@ typedef npy_long __pyx_t_5numpy_int_t; */ typedef npy_longlong __pyx_t_5numpy_long_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":749 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":749 * ctypedef npy_long int_t * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< @@ -592,7 +651,7 @@ typedef npy_longlong __pyx_t_5numpy_long_t; */ typedef npy_longlong __pyx_t_5numpy_longlong_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":751 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":751 * ctypedef npy_longlong longlong_t * * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< @@ -601,7 +660,7 @@ typedef npy_longlong __pyx_t_5numpy_longlong_t; */ typedef npy_ulong __pyx_t_5numpy_uint_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":752 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":752 * * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< @@ -610,7 +669,7 @@ typedef npy_ulong __pyx_t_5numpy_uint_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":753 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":753 * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< @@ -619,7 +678,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":755 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":755 * ctypedef npy_ulonglong ulonglong_t * * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< @@ -628,7 +687,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; */ typedef npy_intp __pyx_t_5numpy_intp_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":756 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":756 * * ctypedef npy_intp intp_t * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< @@ -637,7 +696,7 @@ typedef npy_intp __pyx_t_5numpy_intp_t; */ typedef npy_uintp __pyx_t_5numpy_uintp_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":758 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":758 * ctypedef npy_uintp uintp_t * * ctypedef npy_double float_t # <<<<<<<<<<<<<< @@ -646,7 +705,7 @@ typedef npy_uintp __pyx_t_5numpy_uintp_t; */ typedef npy_double __pyx_t_5numpy_float_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":759 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":759 * * ctypedef npy_double float_t * ctypedef npy_double double_t # <<<<<<<<<<<<<< @@ -655,7 +714,7 @@ typedef npy_double __pyx_t_5numpy_float_t; */ typedef npy_double __pyx_t_5numpy_double_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":760 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":760 * ctypedef npy_double float_t * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< @@ -664,8 +723,8 @@ typedef npy_double __pyx_t_5numpy_double_t; */ typedef npy_longdouble __pyx_t_5numpy_longdouble_t; -/* "GPy/kern/_src/stationary_cython.pyx":6 - * cimport numpy as np +/* "GPy/kern/_src/stationary_cython.pyx":8 + * from cython.parallel import prange * * ctypedef np.float64_t DTYPE_t # <<<<<<<<<<<<<< * @@ -694,8 +753,12 @@ typedef __pyx_t_5numpy_float64_t __pyx_t_3GPy_4kern_4_src_17stationary_cython_DT /*--- Type declarations ---*/ +struct __pyx_array_obj; +struct __pyx_MemviewEnum_obj; +struct __pyx_memoryview_obj; +struct __pyx_memoryviewslice_obj; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":762 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":762 * ctypedef npy_longdouble longdouble_t * * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< @@ -704,7 +767,7 @@ typedef __pyx_t_5numpy_float64_t __pyx_t_3GPy_4kern_4_src_17stationary_cython_DT */ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":763 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":763 * * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< @@ -713,7 +776,7 @@ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; */ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":764 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":764 * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< @@ -722,7 +785,7 @@ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; */ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":766 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":766 * ctypedef npy_clongdouble clongdouble_t * * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< @@ -730,6 +793,116 @@ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; * cdef inline object PyArray_MultiIterNew1(a): */ typedef npy_cdouble __pyx_t_5numpy_complex_t; + +/* "View.MemoryView":99 + * + * @cname("__pyx_array") + * cdef class array: # <<<<<<<<<<<<<< + * + * cdef: + */ +struct __pyx_array_obj { + PyObject_HEAD + char *data; + Py_ssize_t len; + char *format; + int ndim; + Py_ssize_t *_shape; + Py_ssize_t *_strides; + Py_ssize_t itemsize; + PyObject *mode; + PyObject *_format; + void (*callback_free_data)(void *); + int free_data; + int dtype_is_object; +}; + + +/* "View.MemoryView":269 + * + * @cname('__pyx_MemviewEnum') + * cdef class Enum(object): # <<<<<<<<<<<<<< + * cdef object name + * def __init__(self, name): + */ +struct __pyx_MemviewEnum_obj { + PyObject_HEAD + PyObject *name; +}; + + +/* "View.MemoryView":302 + * + * @cname('__pyx_memoryview') + * cdef class memoryview(object): # <<<<<<<<<<<<<< + * + * cdef object obj + */ +struct __pyx_memoryview_obj { + PyObject_HEAD + struct __pyx_vtabstruct_memoryview *__pyx_vtab; + PyObject *obj; + PyObject *_size; + PyObject *_array_interface; + PyThread_type_lock lock; + __pyx_atomic_int acquisition_count[2]; + __pyx_atomic_int *acquisition_count_aligned_p; + Py_buffer view; + int flags; + int dtype_is_object; + __Pyx_TypeInfo *typeinfo; +}; + + +/* "View.MemoryView":922 + * + * @cname('__pyx_memoryviewslice') + * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< + * "Internal class for passing memoryview slices to Python" + * + */ +struct __pyx_memoryviewslice_obj { + struct __pyx_memoryview_obj __pyx_base; + __Pyx_memviewslice from_slice; + PyObject *from_object; + PyObject *(*to_object_func)(char *); + int (*to_dtype_func)(char *, PyObject *); +}; + + + +/* "View.MemoryView":302 + * + * @cname('__pyx_memoryview') + * cdef class memoryview(object): # <<<<<<<<<<<<<< + * + * cdef object obj + */ + +struct __pyx_vtabstruct_memoryview { + char *(*get_item_pointer)(struct __pyx_memoryview_obj *, PyObject *); + PyObject *(*is_slice)(struct __pyx_memoryview_obj *, PyObject *); + PyObject *(*setitem_slice_assignment)(struct __pyx_memoryview_obj *, PyObject *, PyObject *); + PyObject *(*setitem_slice_assign_scalar)(struct __pyx_memoryview_obj *, struct __pyx_memoryview_obj *, PyObject *); + PyObject *(*setitem_indexed)(struct __pyx_memoryview_obj *, PyObject *, PyObject *); + PyObject *(*convert_item_to_object)(struct __pyx_memoryview_obj *, char *); + PyObject *(*assign_item_from_object)(struct __pyx_memoryview_obj *, char *, PyObject *); +}; +static struct __pyx_vtabstruct_memoryview *__pyx_vtabptr_memoryview; + + +/* "View.MemoryView":922 + * + * @cname('__pyx_memoryviewslice') + * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< + * "Internal class for passing memoryview slices to Python" + * + */ + +struct __pyx_vtabstruct__memoryviewslice { + struct __pyx_vtabstruct_memoryview __pyx_base; +}; +static struct __pyx_vtabstruct__memoryviewslice *__pyx_vtabptr__memoryviewslice; #ifndef CYTHON_REFNANNY #define CYTHON_REFNANNY 0 #endif @@ -792,6 +965,23 @@ typedef npy_cdouble __pyx_t_5numpy_complex_t; #define __Pyx_CLEAR(r) do { PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);} while(0) #define __Pyx_XCLEAR(r) do { if((r) != NULL) {PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);}} while(0) +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name) { + PyTypeObject* tp = Py_TYPE(obj); + if (likely(tp->tp_getattro)) + return tp->tp_getattro(obj, attr_name); +#if PY_MAJOR_VERSION < 3 + if (likely(tp->tp_getattr)) + return tp->tp_getattr(obj, PyString_AS_STRING(attr_name)); +#endif + return PyObject_GetAttr(obj, attr_name); +} +#else +#define __Pyx_PyObject_GetAttrStr(o,n) PyObject_GetAttr(o,n) +#endif + +static PyObject *__Pyx_GetBuiltinName(PyObject *name); + static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact, Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found); @@ -811,22 +1001,40 @@ static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info); static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb); static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb); -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name) { - PyTypeObject* tp = Py_TYPE(obj); - if (likely(tp->tp_getattro)) - return tp->tp_getattro(obj, attr_name); -#if PY_MAJOR_VERSION < 3 - if (likely(tp->tp_getattr)) - return tp->tp_getattr(obj, PyString_AS_STRING(attr_name)); -#endif - return PyObject_GetAttr(obj, attr_name); -} -#else -#define __Pyx_PyObject_GetAttrStr(o,n) PyObject_GetAttr(o,n) +static CYTHON_INLINE int __Pyx_div_int(int, int); /* proto */ + +#ifndef __PYX_FORCE_INIT_THREADS + #define __PYX_FORCE_INIT_THREADS 0 #endif -static PyObject *__Pyx_GetBuiltinName(PyObject *name); +#define UNARY_NEG_WOULD_OVERFLOW(x) (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x))) + +static CYTHON_INLINE int __Pyx_mod_int(int, int); /* proto */ + +#define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d +#define __Pyx_MEMVIEW_DIRECT 1 +#define __Pyx_MEMVIEW_PTR 2 +#define __Pyx_MEMVIEW_FULL 4 +#define __Pyx_MEMVIEW_CONTIG 8 +#define __Pyx_MEMVIEW_STRIDED 16 +#define __Pyx_MEMVIEW_FOLLOW 32 +#define __Pyx_IS_C_CONTIG 1 +#define __Pyx_IS_F_CONTIG 2 +static int __Pyx_init_memviewslice( + struct __pyx_memoryview_obj *memview, + int ndim, + __Pyx_memviewslice *memviewslice, + int memview_is_new_reference); +static CYTHON_INLINE int __pyx_add_acquisition_count_locked( + __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); +static CYTHON_INLINE int __pyx_sub_acquisition_count_locked( + __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); +#define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p) +#define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview)) +#define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__) +#define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__) +static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int); +static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int); #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw); @@ -844,6 +1052,128 @@ static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); +#include + +static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals); + +static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals); + +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyString_Equals __Pyx_PyUnicode_Equals +#else +#define __Pyx_PyString_Equals __Pyx_PyBytes_Equals +#endif + +static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t, Py_ssize_t); /* proto */ + +static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ +static PyObject *get_memview(PyObject *__pyx_v_self); /*proto*/ +static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *); + +static CYTHON_INLINE PyObject* __Pyx_decode_c_string( + const char* cstring, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)); + +static CYTHON_INLINE void __Pyx_ExceptionSave(PyObject **type, PyObject **value, PyObject **tb); +static void __Pyx_ExceptionReset(PyObject *type, PyObject *value, PyObject *tb); + +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); + +static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb); + +#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \ + __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) : \ + (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) : \ + __Pyx_GetItemInt_Generic(o, to_py_func(i)))) +#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \ + __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) : \ + (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \ + __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) : \ + (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j); +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, + int is_list, int wraparound, int boundscheck); + +static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ +static PyObject *__pyx_memoryview_transpose(PyObject *__pyx_v_self); /*proto*/ +static PyObject *__pyx_memoryview__get__base(PyObject *__pyx_v_self); /*proto*/ +static PyObject *__pyx_memoryview_get_shape(PyObject *__pyx_v_self); /*proto*/ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { + PyListObject* L = (PyListObject*) list; + Py_ssize_t len = Py_SIZE(list); + if (likely(L->allocated > len)) { + Py_INCREF(x); + PyList_SET_ITEM(list, len, x); + Py_SIZE(list) = len+1; + return 0; + } + return PyList_Append(list, x); +} +#else +#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x) +#endif + +static PyObject *__pyx_memoryview_get_strides(PyObject *__pyx_v_self); /*proto*/ +static PyObject *__pyx_memoryview_get_suboffsets(PyObject *__pyx_v_self); /*proto*/ +static PyObject *__pyx_memoryview_get_ndim(PyObject *__pyx_v_self); /*proto*/ +static PyObject *__pyx_memoryview_get_itemsize(PyObject *__pyx_v_self); /*proto*/ +static PyObject *__pyx_memoryview_get_nbytes(PyObject *__pyx_v_self); /*proto*/ +static PyObject *__pyx_memoryview_get_size(PyObject *__pyx_v_self); /*proto*/ +static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) { +#if CYTHON_COMPILING_IN_CPYTHON + PyObject* none = _PyList_Extend((PyListObject*)L, v); + if (unlikely(!none)) + return -1; + Py_DECREF(none); + return 0; +#else + return PyList_SetSlice(L, PY_SSIZE_T_MAX, PY_SSIZE_T_MAX, v); +#endif +} + +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { + PyListObject* L = (PyListObject*) list; + Py_ssize_t len = Py_SIZE(list); + if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) { + Py_INCREF(x); + PyList_SET_ITEM(list, len, x); + Py_SIZE(list) = len+1; + return 0; + } + return PyList_Append(list, x); +} +#else +#define __Pyx_PyList_Append(L,x) PyList_Append(L,x) +#endif + +static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname); + +static CYTHON_INLINE long __Pyx_div_long(long, long); /* proto */ + +static PyObject *__pyx_memoryviewslice__get__base(PyObject *__pyx_v_self); /*proto*/ +static void __Pyx_WriteUnraisable(const char *name, int clineno, + int lineno, const char *filename, + int full_traceback); + +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg); +#endif + +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); + +static int __Pyx_SetVtable(PyObject *dict, void *vtable); + typedef struct { int code_line; PyCodeObject* code_object; @@ -890,6 +1220,24 @@ static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); +static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b); + +static int __Pyx_ValidateAndInit_memviewslice( + int *axes_specs, + int c_or_f_flag, + int buf_flags, + int ndim, + __Pyx_TypeInfo *dtype, + __Pyx_BufFmt_StackElem stack[], + __Pyx_memviewslice *memviewslice, + PyObject *original_obj); + +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_double(PyObject *); + +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_double(PyObject *); + +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); + #if CYTHON_CCOMPLEX #ifdef __cplusplus #define __Pyx_CREAL(z) ((z).real()) @@ -988,10 +1336,25 @@ static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(do #endif #endif -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); +static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice *mvs, + char order, int ndim); + +static int __pyx_slices_overlap(__Pyx_memviewslice *slice1, + __Pyx_memviewslice *slice2, + int ndim, size_t itemsize); + +static __Pyx_memviewslice +__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, + const char *mode, int ndim, + size_t sizeof_dtype, int contig_flag, + int dtype_is_object); + +static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig); static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); +static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *); + static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); static int __Pyx_check_binary_version(void); @@ -1010,6 +1373,15 @@ static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); +static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ +static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/ +static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/ +static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ +static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ +static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ /* Module declarations from 'cpython.buffer' */ @@ -1039,18 +1411,105 @@ static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *, char *, char *, int *); /*proto*/ /* Module declarations from 'GPy.kern._src.stationary_cython' */ +static PyTypeObject *__pyx_array_type = 0; +static PyTypeObject *__pyx_MemviewEnum_type = 0; +static PyTypeObject *__pyx_memoryview_type = 0; +static PyTypeObject *__pyx_memoryviewslice_type = 0; +static PyObject *generic = 0; +static PyObject *strided = 0; +static PyObject *indirect = 0; +static PyObject *contiguous = 0; +static PyObject *indirect_contiguous = 0; +static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/ +static void *__pyx_align_pointer(void *, size_t); /*proto*/ +static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/ +static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/ +static PyObject *_unellipsify(PyObject *, int); /*proto*/ +static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/ +static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/ +static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/ +static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/ +static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/ +static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/ +static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/ +static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/ +static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/ +static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/ +static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/ +static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/ +static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/ +static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/ +static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/ +static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/ +static int __pyx_memoryview_err(PyObject *, char *); /*proto*/ +static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/ +static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/ +static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/ +static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ +static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ +static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/ +static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/ static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t = { "DTYPE_t", NULL, sizeof(__pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t), { 0 }, 0, 'R', 0, 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_double = { "double", NULL, sizeof(double), { 0 }, 0, 'R', 0, 0 }; #define __Pyx_MODULE_NAME "GPy.kern._src.stationary_cython" int __pyx_module_is_main_GPy__kern___src__stationary_cython = 0; /* Implementation of 'GPy.kern._src.stationary_cython' */ -static PyObject *__pyx_builtin_ValueError; static PyObject *__pyx_builtin_range; +static PyObject *__pyx_builtin_ValueError; static PyObject *__pyx_builtin_RuntimeError; +static PyObject *__pyx_builtin_MemoryError; +static PyObject *__pyx_builtin_enumerate; +static PyObject *__pyx_builtin_Ellipsis; +static PyObject *__pyx_builtin_TypeError; +static PyObject *__pyx_builtin_xrange; +static PyObject *__pyx_builtin_id; +static PyObject *__pyx_builtin_IndexError; static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_grad_X(CYTHON_UNUSED PyObject *__pyx_self, int __pyx_v_N, int __pyx_v_D, int __pyx_v_M, PyArrayObject *__pyx_v__X, PyArrayObject *__pyx_v__X2, PyArrayObject *__pyx_v__tmp, PyArrayObject *__pyx_v__grad); /* proto */ -static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_2lengthscale_grads(CYTHON_UNUSED PyObject *__pyx_self, int __pyx_v_N, int __pyx_v_M, int __pyx_v_Q, PyArrayObject *__pyx_v__tmp, PyArrayObject *__pyx_v__X, PyArrayObject *__pyx_v__X2, PyArrayObject *__pyx_v__grad); /* proto */ +static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_2grad_X_cython(CYTHON_UNUSED PyObject *__pyx_self, CYTHON_UNUSED int __pyx_v_N, int __pyx_v_D, int __pyx_v_M, __Pyx_memviewslice __pyx_v_X, __Pyx_memviewslice __pyx_v_X2, __Pyx_memviewslice __pyx_v_tmp, __Pyx_memviewslice __pyx_v_grad); /* proto */ +static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_4lengthscale_grads_in_c(CYTHON_UNUSED PyObject *__pyx_self, int __pyx_v_N, int __pyx_v_M, int __pyx_v_Q, PyArrayObject *__pyx_v__tmp, PyArrayObject *__pyx_v__X, PyArrayObject *__pyx_v__X2, PyArrayObject *__pyx_v__grad); /* proto */ +static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_6lengthscale_grads(CYTHON_UNUSED PyObject *__pyx_self, int __pyx_v_N, int __pyx_v_M, int __pyx_v_Q, __Pyx_memviewslice __pyx_v_tmp, __Pyx_memviewslice __pyx_v_X, __Pyx_memviewslice __pyx_v_X2, __Pyx_memviewslice __pyx_v_grad); /* proto */ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */ +static int __pyx_array_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ +static int __pyx_array_getbuffer_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static void __pyx_array_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *get_memview_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_array_MemoryView_5array_6__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */ +static PyObject *__pyx_array_MemoryView_5array_8__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */ +static int __pyx_array_MemoryView_5array_10__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */ +static int __pyx_MemviewEnum_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */ +static PyObject *__pyx_MemviewEnum_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ +static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */ +static void __pyx_memoryview_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */ +static int __pyx_memoryview_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */ +static int __pyx_memoryview_getbuffer_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static PyObject *__pyx_memoryview_transpose_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview__get__base_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_get_shape_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_get_strides_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_get_suboffsets_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_get_ndim_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_get_itemsize_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_get_nbytes_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_get_size_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static Py_ssize_t __pyx_memoryview_MemoryView_10memoryview_10__len__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_MemoryView_10memoryview_12__repr__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_MemoryView_10memoryview_14__str__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_MemoryView_10memoryview_16is_c_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_MemoryView_10memoryview_18is_f_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_MemoryView_10memoryview_20copy(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_MemoryView_10memoryview_22copy_fortran(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static void __pyx_memoryviewslice_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryviewslice__get__base_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static char __pyx_k_B[] = "B"; static char __pyx_k_D[] = "D"; static char __pyx_k_H[] = "H"; @@ -1062,71 +1521,205 @@ static char __pyx_k_O[] = "O"; static char __pyx_k_Q[] = "Q"; static char __pyx_k_X[] = "_X"; static char __pyx_k_b[] = "b"; +static char __pyx_k_c[] = "c"; static char __pyx_k_d[] = "d"; static char __pyx_k_f[] = "f"; static char __pyx_k_g[] = "g"; static char __pyx_k_h[] = "h"; static char __pyx_k_i[] = "i"; static char __pyx_k_l[] = "l"; +static char __pyx_k_m[] = "m"; +static char __pyx_k_n[] = "n"; static char __pyx_k_q[] = "q"; static char __pyx_k_X2[] = "_X2"; static char __pyx_k_Zd[] = "Zd"; static char __pyx_k_Zf[] = "Zf"; static char __pyx_k_Zg[] = "Zg"; +static char __pyx_k_id[] = "id"; +static char __pyx_k_nd[] = "nd"; static char __pyx_k_np[] = "np"; static char __pyx_k_X_2[] = "X"; +static char __pyx_k_obj[] = "obj"; static char __pyx_k_tmp[] = "_tmp"; static char __pyx_k_X2_2[] = "X2"; +static char __pyx_k_base[] = "base"; +static char __pyx_k_dist[] = "dist"; static char __pyx_k_grad[] = "_grad"; static char __pyx_k_main[] = "__main__"; +static char __pyx_k_mode[] = "mode"; +static char __pyx_k_name[] = "name"; +static char __pyx_k_ndim[] = "ndim"; +static char __pyx_k_pack[] = "pack"; +static char __pyx_k_size[] = "size"; +static char __pyx_k_step[] = "step"; +static char __pyx_k_stop[] = "stop"; static char __pyx_k_test[] = "__test__"; +static char __pyx_k_class[] = "__class__"; +static char __pyx_k_error[] = "error"; +static char __pyx_k_flags[] = "flags"; +static char __pyx_k_gradq[] = "gradq"; static char __pyx_k_numpy[] = "numpy"; static char __pyx_k_range[] = "range"; +static char __pyx_k_shape[] = "shape"; +static char __pyx_k_start[] = "start"; static char __pyx_k_tmp_2[] = "tmp"; +static char __pyx_k_format[] = "format"; static char __pyx_k_grad_2[] = "grad"; static char __pyx_k_grad_X[] = "grad_X"; static char __pyx_k_import[] = "__import__"; +static char __pyx_k_name_2[] = "__name__"; +static char __pyx_k_struct[] = "struct"; +static char __pyx_k_unpack[] = "unpack"; +static char __pyx_k_xrange[] = "xrange"; +static char __pyx_k_fortran[] = "fortran"; +static char __pyx_k_memview[] = "memview"; +static char __pyx_k_Ellipsis[] = "Ellipsis"; +static char __pyx_k_itemsize[] = "itemsize"; +static char __pyx_k_TypeError[] = "TypeError"; +static char __pyx_k_enumerate[] = "enumerate"; +static char __pyx_k_IndexError[] = "IndexError"; static char __pyx_k_ValueError[] = "ValueError"; +static char __pyx_k_pyx_vtable[] = "__pyx_vtable__"; +static char __pyx_k_MemoryError[] = "MemoryError"; static char __pyx_k_RuntimeError[] = "RuntimeError"; +static char __pyx_k_grad_X_cython[] = "grad_X_cython"; +static char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer"; +static char __pyx_k_allocate_buffer[] = "allocate_buffer"; +static char __pyx_k_dtype_is_object[] = "dtype_is_object"; static char __pyx_k_lengthscale_grads[] = "lengthscale_grads"; +static char __pyx_k_strided_and_direct[] = ""; +static char __pyx_k_strided_and_indirect[] = ""; +static char __pyx_k_contiguous_and_direct[] = ""; +static char __pyx_k_MemoryView_of_r_object[] = ""; +static char __pyx_k_lengthscale_grads_in_c[] = "lengthscale_grads_in_c"; +static char __pyx_k_MemoryView_of_r_at_0x_x[] = ""; +static char __pyx_k_contiguous_and_indirect[] = ""; +static char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'"; +static char __pyx_k_getbuffer_obj_view_flags[] = "getbuffer(obj, view, flags)"; +static char __pyx_k_Dimension_d_is_not_direct[] = "Dimension %d is not direct"; +static char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d."; +static char __pyx_k_Index_out_of_bounds_axis_d[] = "Index out of bounds (axis %d)"; +static char __pyx_k_Step_may_not_be_zero_axis_d[] = "Step may not be zero (axis %d)"; +static char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array"; static char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous"; +static char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; +static char __pyx_k_strided_and_direct_or_indirect[] = ""; static char __pyx_k_GPy_kern__src_stationary_cython[] = "GPy.kern._src.stationary_cython"; static char __pyx_k_home_james_work_GPy_GPy_kern__s[] = "/home/james/work/GPy/GPy/kern/_src/stationary_cython.pyx"; static char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)"; +static char __pyx_k_All_dimensions_preceding_dimensi[] = "All dimensions preceding dimension %d must be indexed and not sliced"; +static char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; +static char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory."; +static char __pyx_k_Cannot_transpose_memoryview_with[] = "Cannot transpose memoryview with indirect dimensions"; +static char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array"; static char __pyx_k_Format_string_allocated_too_shor[] = "Format string allocated too short, see comment in numpy.pxd"; +static char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported"; +static char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s"; static char __pyx_k_Non_native_byte_order_not_suppor[] = "Non-native byte order not supported"; +static char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)"; +static char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object"; +static char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)"; static char __pyx_k_ndarray_is_not_Fortran_contiguou[] = "ndarray is not Fortran contiguous"; +static char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides."; static char __pyx_k_Format_string_allocated_too_shor_2[] = "Format string allocated too short."; +static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri; +static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is; +static PyObject *__pyx_kp_s_Cannot_index_with_type_s; static PyObject *__pyx_n_s_D; +static PyObject *__pyx_n_s_Ellipsis; +static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr; static PyObject *__pyx_kp_u_Format_string_allocated_too_shor; static PyObject *__pyx_kp_u_Format_string_allocated_too_shor_2; static PyObject *__pyx_n_s_GPy_kern__src_stationary_cython; +static PyObject *__pyx_n_s_IndexError; +static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte; +static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr; +static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d; static PyObject *__pyx_n_s_M; +static PyObject *__pyx_n_s_MemoryError; +static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x; +static PyObject *__pyx_kp_s_MemoryView_of_r_object; static PyObject *__pyx_n_s_N; static PyObject *__pyx_kp_u_Non_native_byte_order_not_suppor; +static PyObject *__pyx_n_b_O; +static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a; static PyObject *__pyx_n_s_Q; static PyObject *__pyx_n_s_RuntimeError; +static PyObject *__pyx_n_s_TypeError; +static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object; static PyObject *__pyx_n_s_ValueError; static PyObject *__pyx_n_s_X; static PyObject *__pyx_n_s_X2; static PyObject *__pyx_n_s_X2_2; static PyObject *__pyx_n_s_X_2; +static PyObject *__pyx_n_s_allocate_buffer; +static PyObject *__pyx_n_s_base; +static PyObject *__pyx_n_s_c; +static PyObject *__pyx_n_u_c; +static PyObject *__pyx_n_s_class; +static PyObject *__pyx_kp_s_contiguous_and_direct; +static PyObject *__pyx_kp_s_contiguous_and_indirect; +static PyObject *__pyx_n_s_d; +static PyObject *__pyx_n_s_dist; +static PyObject *__pyx_n_s_dtype_is_object; +static PyObject *__pyx_n_s_enumerate; +static PyObject *__pyx_n_s_error; +static PyObject *__pyx_n_s_flags; +static PyObject *__pyx_n_s_format; +static PyObject *__pyx_n_s_fortran; +static PyObject *__pyx_n_u_fortran; +static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi; static PyObject *__pyx_n_s_grad; static PyObject *__pyx_n_s_grad_2; static PyObject *__pyx_n_s_grad_X; +static PyObject *__pyx_n_s_grad_X_cython; +static PyObject *__pyx_n_s_gradq; static PyObject *__pyx_kp_s_home_james_work_GPy_GPy_kern__s; +static PyObject *__pyx_n_s_id; static PyObject *__pyx_n_s_import; +static PyObject *__pyx_n_s_itemsize; +static PyObject *__pyx_kp_s_itemsize_0_for_cython_array; static PyObject *__pyx_n_s_lengthscale_grads; +static PyObject *__pyx_n_s_lengthscale_grads_in_c; +static PyObject *__pyx_n_s_m; static PyObject *__pyx_n_s_main; +static PyObject *__pyx_n_s_memview; +static PyObject *__pyx_n_s_mode; +static PyObject *__pyx_n_s_n; +static PyObject *__pyx_n_s_name; +static PyObject *__pyx_n_s_name_2; +static PyObject *__pyx_n_s_nd; static PyObject *__pyx_kp_u_ndarray_is_not_C_contiguous; static PyObject *__pyx_kp_u_ndarray_is_not_Fortran_contiguou; +static PyObject *__pyx_n_s_ndim; static PyObject *__pyx_n_s_np; static PyObject *__pyx_n_s_numpy; +static PyObject *__pyx_n_s_obj; +static PyObject *__pyx_n_s_pack; +static PyObject *__pyx_n_s_pyx_getbuffer; +static PyObject *__pyx_n_s_pyx_vtable; +static PyObject *__pyx_n_s_q; static PyObject *__pyx_n_s_range; +static PyObject *__pyx_n_s_shape; +static PyObject *__pyx_n_s_size; +static PyObject *__pyx_n_s_start; +static PyObject *__pyx_n_s_step; +static PyObject *__pyx_n_s_stop; +static PyObject *__pyx_kp_s_strided_and_direct; +static PyObject *__pyx_kp_s_strided_and_direct_or_indirect; +static PyObject *__pyx_kp_s_strided_and_indirect; +static PyObject *__pyx_n_s_struct; static PyObject *__pyx_n_s_test; static PyObject *__pyx_n_s_tmp; static PyObject *__pyx_n_s_tmp_2; +static PyObject *__pyx_kp_s_unable_to_allocate_array_data; +static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str; static PyObject *__pyx_kp_u_unknown_dtype_code_in_numpy_pxd; +static PyObject *__pyx_n_s_unpack; +static PyObject *__pyx_n_s_xrange; +static PyObject *__pyx_int_0; +static PyObject *__pyx_int_1; +static PyObject *__pyx_int_neg_1; static PyObject *__pyx_tuple_; static PyObject *__pyx_tuple__2; static PyObject *__pyx_tuple__3; @@ -1134,11 +1727,31 @@ static PyObject *__pyx_tuple__4; static PyObject *__pyx_tuple__5; static PyObject *__pyx_tuple__6; static PyObject *__pyx_tuple__7; +static PyObject *__pyx_tuple__8; static PyObject *__pyx_tuple__9; -static PyObject *__pyx_codeobj__8; -static PyObject *__pyx_codeobj__10; +static PyObject *__pyx_slice__14; +static PyObject *__pyx_slice__15; +static PyObject *__pyx_slice__16; +static PyObject *__pyx_tuple__10; +static PyObject *__pyx_tuple__11; +static PyObject *__pyx_tuple__12; +static PyObject *__pyx_tuple__13; +static PyObject *__pyx_tuple__17; +static PyObject *__pyx_tuple__18; +static PyObject *__pyx_tuple__20; +static PyObject *__pyx_tuple__22; +static PyObject *__pyx_tuple__24; +static PyObject *__pyx_tuple__26; +static PyObject *__pyx_tuple__27; +static PyObject *__pyx_tuple__28; +static PyObject *__pyx_tuple__29; +static PyObject *__pyx_tuple__30; +static PyObject *__pyx_codeobj__19; +static PyObject *__pyx_codeobj__21; +static PyObject *__pyx_codeobj__23; +static PyObject *__pyx_codeobj__25; -/* "GPy/kern/_src/stationary_cython.pyx":14 +/* "GPy/kern/_src/stationary_cython.pyx":16 * void _lengthscale_grads "_lengthscale_grads" (int N, int M, int Q, double* tmp, double* X, double* X2, double* grad) * * def grad_X(int N, int D, int M, # <<<<<<<<<<<<<< @@ -1188,36 +1801,36 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_17stationary_cython_1grad_X(PyObject case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_D)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 14; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 2: if (likely((values[2] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_M)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 14; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 3: if (likely((values[3] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_X)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 14; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 4: if (likely((values[4] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_X2)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 14; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 5: if (likely((values[5] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_tmp)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 14; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 6: if (likely((values[6] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_grad)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 14; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "grad_X") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 14; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "grad_X") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else if (PyTuple_GET_SIZE(__pyx_args) != 7) { goto __pyx_L5_argtuple_error; @@ -1230,9 +1843,9 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_17stationary_cython_1grad_X(PyObject values[5] = PyTuple_GET_ITEM(__pyx_args, 5); values[6] = PyTuple_GET_ITEM(__pyx_args, 6); } - __pyx_v_N = __Pyx_PyInt_As_int(values[0]); if (unlikely((__pyx_v_N == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 14; __pyx_clineno = __LINE__; goto __pyx_L3_error;} - __pyx_v_D = __Pyx_PyInt_As_int(values[1]); if (unlikely((__pyx_v_D == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 14; __pyx_clineno = __LINE__; goto __pyx_L3_error;} - __pyx_v_M = __Pyx_PyInt_As_int(values[2]); if (unlikely((__pyx_v_M == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 14; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_N = __Pyx_PyInt_As_int(values[0]); if (unlikely((__pyx_v_N == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_D = __Pyx_PyInt_As_int(values[1]); if (unlikely((__pyx_v_D == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_M = __Pyx_PyInt_As_int(values[2]); if (unlikely((__pyx_v_M == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_v__X = ((PyArrayObject *)values[3]); __pyx_v__X2 = ((PyArrayObject *)values[4]); __pyx_v__tmp = ((PyArrayObject *)values[5]); @@ -1240,16 +1853,16 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_17stationary_cython_1grad_X(PyObject } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 14; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("grad_X", 1, 7, 7, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("GPy.kern._src.stationary_cython.grad_X", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return NULL; __pyx_L4_argument_unpacking_done:; - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__X), __pyx_ptype_5numpy_ndarray, 1, "_X", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 15; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__X2), __pyx_ptype_5numpy_ndarray, 1, "_X2", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__tmp), __pyx_ptype_5numpy_ndarray, 1, "_tmp", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__grad), __pyx_ptype_5numpy_ndarray, 1, "_grad", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 18; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__X), __pyx_ptype_5numpy_ndarray, 1, "_X", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__X2), __pyx_ptype_5numpy_ndarray, 1, "_X2", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 18; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__tmp), __pyx_ptype_5numpy_ndarray, 1, "_tmp", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 19; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v__grad), __pyx_ptype_5numpy_ndarray, 1, "_grad", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_r = __pyx_pf_3GPy_4kern_4_src_17stationary_cython_grad_X(__pyx_self, __pyx_v_N, __pyx_v_D, __pyx_v_M, __pyx_v__X, __pyx_v__X2, __pyx_v__tmp, __pyx_v__grad); /* function exit code */ @@ -1298,26 +1911,26 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_grad_X(CYTHON_UNU __pyx_pybuffernd__grad.rcbuffer = &__pyx_pybuffer__grad; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__X.rcbuffer->pybuffer, (PyObject*)__pyx_v__X, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 14; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__X.rcbuffer->pybuffer, (PyObject*)__pyx_v__X, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd__X.diminfo[0].strides = __pyx_pybuffernd__X.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd__X.diminfo[0].shape = __pyx_pybuffernd__X.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd__X.diminfo[1].strides = __pyx_pybuffernd__X.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd__X.diminfo[1].shape = __pyx_pybuffernd__X.rcbuffer->pybuffer.shape[1]; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__X2.rcbuffer->pybuffer, (PyObject*)__pyx_v__X2, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 14; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__X2.rcbuffer->pybuffer, (PyObject*)__pyx_v__X2, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd__X2.diminfo[0].strides = __pyx_pybuffernd__X2.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd__X2.diminfo[0].shape = __pyx_pybuffernd__X2.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd__X2.diminfo[1].strides = __pyx_pybuffernd__X2.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd__X2.diminfo[1].shape = __pyx_pybuffernd__X2.rcbuffer->pybuffer.shape[1]; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__tmp.rcbuffer->pybuffer, (PyObject*)__pyx_v__tmp, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 14; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__tmp.rcbuffer->pybuffer, (PyObject*)__pyx_v__tmp, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd__tmp.diminfo[0].strides = __pyx_pybuffernd__tmp.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd__tmp.diminfo[0].shape = __pyx_pybuffernd__tmp.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd__tmp.diminfo[1].strides = __pyx_pybuffernd__tmp.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd__tmp.diminfo[1].shape = __pyx_pybuffernd__tmp.rcbuffer->pybuffer.shape[1]; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__grad.rcbuffer->pybuffer, (PyObject*)__pyx_v__grad, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 14; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__grad.rcbuffer->pybuffer, (PyObject*)__pyx_v__grad, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 16; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd__grad.diminfo[0].strides = __pyx_pybuffernd__grad.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd__grad.diminfo[0].shape = __pyx_pybuffernd__grad.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd__grad.diminfo[1].strides = __pyx_pybuffernd__grad.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd__grad.diminfo[1].shape = __pyx_pybuffernd__grad.rcbuffer->pybuffer.shape[1]; - /* "GPy/kern/_src/stationary_cython.pyx":19 + /* "GPy/kern/_src/stationary_cython.pyx":21 * np.ndarray[DTYPE_t, ndim=2] _tmp, * np.ndarray[DTYPE_t, ndim=2] _grad): * cdef double *X = _X.data # <<<<<<<<<<<<<< @@ -1326,7 +1939,7 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_grad_X(CYTHON_UNU */ __pyx_v_X = ((double *)__pyx_v__X->data); - /* "GPy/kern/_src/stationary_cython.pyx":20 + /* "GPy/kern/_src/stationary_cython.pyx":22 * np.ndarray[DTYPE_t, ndim=2] _grad): * cdef double *X = _X.data * cdef double *X2 = _X2.data # <<<<<<<<<<<<<< @@ -1335,7 +1948,7 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_grad_X(CYTHON_UNU */ __pyx_v_X2 = ((double *)__pyx_v__X2->data); - /* "GPy/kern/_src/stationary_cython.pyx":21 + /* "GPy/kern/_src/stationary_cython.pyx":23 * cdef double *X = _X.data * cdef double *X2 = _X2.data * cdef double *tmp = _tmp.data # <<<<<<<<<<<<<< @@ -1344,7 +1957,7 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_grad_X(CYTHON_UNU */ __pyx_v_tmp = ((double *)__pyx_v__tmp->data); - /* "GPy/kern/_src/stationary_cython.pyx":22 + /* "GPy/kern/_src/stationary_cython.pyx":24 * cdef double *X2 = _X2.data * cdef double *tmp = _tmp.data * cdef double *grad = _grad.data # <<<<<<<<<<<<<< @@ -1353,16 +1966,16 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_grad_X(CYTHON_UNU */ __pyx_v_grad = ((double *)__pyx_v__grad->data); - /* "GPy/kern/_src/stationary_cython.pyx":23 + /* "GPy/kern/_src/stationary_cython.pyx":25 * cdef double *tmp = _tmp.data * cdef double *grad = _grad.data * _grad_X(N, D, M, X, X2, tmp, grad) # return nothing, work in place. # <<<<<<<<<<<<<< * - * def lengthscale_grads(int N, int M, int Q, + * def grad_X_cython(int N, int D, int M, double[:,:] X, double[:,:] X2, double[:,:] tmp, double[:,:] grad): */ _grad_X(__pyx_v_N, __pyx_v_D, __pyx_v_M, __pyx_v_X, __pyx_v_X2, __pyx_v_tmp, __pyx_v_grad); 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__builtin_expect(!!(x), 0) + #endif + } + + /* "GPy/kern/_src/stationary_cython.pyx":29 + * def grad_X_cython(int N, int D, int M, double[:,:] X, double[:,:] X2, double[:,:] tmp, double[:,:] grad): + * cdef int n,d,nd,m + * for nd in prange(N*D, nogil=True): # <<<<<<<<<<<<<< + * n = nd/D + * d = nd%D + */ + /*finally:*/ { + /*normal exit:*/{ + #ifdef WITH_THREAD + Py_BLOCK_THREADS + #endif + goto __pyx_L5; + } + __pyx_L3_return: { + #ifdef WITH_THREAD + Py_BLOCK_THREADS + #endif + goto __pyx_L0; + } + __pyx_L4_error: { + #ifdef WITH_THREAD + Py_BLOCK_THREADS + #endif + goto __pyx_L1_error; + } + __pyx_L5:; + } + } + + /* "GPy/kern/_src/stationary_cython.pyx":27 + * _grad_X(N, D, M, X, X2, tmp, grad) # return nothing, work in place. + * + * def grad_X_cython(int N, int D, int M, double[:,:] X, double[:,:] X2, double[:,:] tmp, double[:,:] grad): # <<<<<<<<<<<<<< + * cdef int n,d,nd,m + * for nd in prange(N*D, nogil=True): + */ + + /* function exit code */ + __pyx_r = Py_None; __Pyx_INCREF(Py_None); + goto __pyx_L0; + __pyx_L1_error:; + __Pyx_AddTraceback("GPy.kern._src.stationary_cython.grad_X_cython", __pyx_clineno, __pyx_lineno, __pyx_filename); + __pyx_r = NULL; + __pyx_L0:; + __PYX_XDEC_MEMVIEW(&__pyx_v_X, 1); + __PYX_XDEC_MEMVIEW(&__pyx_v_X2, 1); + __PYX_XDEC_MEMVIEW(&__pyx_v_tmp, 1); + __PYX_XDEC_MEMVIEW(&__pyx_v_grad, 1); + __Pyx_XGIVEREF(__pyx_r); + __Pyx_RefNannyFinishContext(); + return __pyx_r; +} + +/* "GPy/kern/_src/stationary_cython.pyx":38 + * + * + * def lengthscale_grads_in_c(int N, int M, int Q, # <<<<<<<<<<<<<< * np.ndarray[DTYPE_t, ndim=2] _tmp, * np.ndarray[DTYPE_t, ndim=2] _X, */ /* Python wrapper */ -static PyObject *__pyx_pw_3GPy_4kern_4_src_17stationary_cython_3lengthscale_grads(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -static PyMethodDef __pyx_mdef_3GPy_4kern_4_src_17stationary_cython_3lengthscale_grads = {"lengthscale_grads", 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*__pyx_r = 0; __Pyx_RefNannyDeclarations - __Pyx_RefNannySetupContext("lengthscale_grads (wrapper)", 0); + __Pyx_RefNannySetupContext("lengthscale_grads_in_c (wrapper)", 0); { static PyObject **__pyx_pyargnames[] = {&__pyx_n_s_N,&__pyx_n_s_M,&__pyx_n_s_Q,&__pyx_n_s_tmp,&__pyx_n_s_X,&__pyx_n_s_X2,&__pyx_n_s_grad,0}; PyObject* values[7] = {0,0,0,0,0,0,0}; @@ -1445,36 +2484,36 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_17stationary_cython_3lengthscale_grad case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_M)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 25; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 2: if (likely((values[2] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_Q)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 25; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 3: if (likely((values[3] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_tmp)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 25; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 4: if (likely((values[4] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_X)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 25; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 5: if (likely((values[5] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_X2)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 25; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 6: if (likely((values[6] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_grad)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 25; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "lengthscale_grads") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 25; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "lengthscale_grads_in_c") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else if (PyTuple_GET_SIZE(__pyx_args) != 7) { goto __pyx_L5_argtuple_error; @@ -1487,9 +2526,9 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_17stationary_cython_3lengthscale_grad values[5] = PyTuple_GET_ITEM(__pyx_args, 5); values[6] = PyTuple_GET_ITEM(__pyx_args, 6); } - __pyx_v_N = __Pyx_PyInt_As_int(values[0]); if (unlikely((__pyx_v_N == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 25; __pyx_clineno = __LINE__; goto __pyx_L3_error;} - 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__pyx_v__tmp = ((PyArrayObject *)values[3]); __pyx_v__X = ((PyArrayObject *)values[4]); __pyx_v__X2 = ((PyArrayObject *)values[5]); @@ -1497,17 +2536,17 @@ static PyObject *__pyx_pw_3GPy_4kern_4_src_17stationary_cython_3lengthscale_grad } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("lengthscale_grads", 1, 7, 7, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 25; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lengthscale_grads_in_c", 1, 7, 7, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; - __Pyx_AddTraceback("GPy.kern._src.stationary_cython.lengthscale_grads", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("GPy.kern._src.stationary_cython.lengthscale_grads_in_c", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return NULL; 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__pyx_f[0]; __pyx_lineno = 25; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd__grad.rcbuffer->pybuffer, (PyObject*)__pyx_v__grad, &__Pyx_TypeInfo_nn___pyx_t_3GPy_4kern_4_src_17stationary_cython_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd__grad.diminfo[0].strides = __pyx_pybuffernd__grad.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd__grad.diminfo[0].shape = __pyx_pybuffernd__grad.rcbuffer->pybuffer.shape[0]; - /* "GPy/kern/_src/stationary_cython.pyx":30 + /* "GPy/kern/_src/stationary_cython.pyx":43 * np.ndarray[DTYPE_t, ndim=2] _X2, * np.ndarray[DTYPE_t, ndim=1] _grad): * cdef double *tmp = _tmp.data # <<<<<<<<<<<<<< @@ -1583,7 +2622,7 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_2lengthscale_grad */ __pyx_v_tmp = ((double *)__pyx_v__tmp->data); - /* "GPy/kern/_src/stationary_cython.pyx":31 + /* "GPy/kern/_src/stationary_cython.pyx":44 * np.ndarray[DTYPE_t, ndim=1] _grad): * cdef double *tmp = _tmp.data * cdef double *X = _X.data # <<<<<<<<<<<<<< @@ -1592,7 +2631,7 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_2lengthscale_grad */ __pyx_v_X = ((double *)__pyx_v__X->data); - /* "GPy/kern/_src/stationary_cython.pyx":32 + /* "GPy/kern/_src/stationary_cython.pyx":45 * cdef double *tmp = _tmp.data * cdef double *X = _X.data * cdef double *X2 = _X2.data # <<<<<<<<<<<<<< @@ -1601,7 +2640,7 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_2lengthscale_grad */ __pyx_v_X2 = ((double *)__pyx_v__X2->data); - /* "GPy/kern/_src/stationary_cython.pyx":33 + /* "GPy/kern/_src/stationary_cython.pyx":46 * cdef double *X = _X.data * cdef double *X2 = _X2.data * cdef double *grad = _grad.data # <<<<<<<<<<<<<< @@ -1610,19 +2649,19 @@ static PyObject *__pyx_pf_3GPy_4kern_4_src_17stationary_cython_2lengthscale_grad */ __pyx_v_grad = ((double *)__pyx_v__grad->data); - /* "GPy/kern/_src/stationary_cython.pyx":34 + /* "GPy/kern/_src/stationary_cython.pyx":47 * cdef double *X2 = _X2.data * cdef double *grad = _grad.data * _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. # <<<<<<<<<<<<<< * - * + * def lengthscale_grads(int N, int M, int Q, double[:,:] tmp, double[:,:] X, double[:,:] X2, double[:] grad): */ _lengthscale_grads(__pyx_v_N, __pyx_v_M, __pyx_v_Q, __pyx_v_tmp, __pyx_v_X, __pyx_v_X2, __pyx_v_grad); - /* "GPy/kern/_src/stationary_cython.pyx":25 - * _grad_X(N, D, M, X, X2, tmp, grad) # return nothing, work in place. + /* "GPy/kern/_src/stationary_cython.pyx":38 * - * def lengthscale_grads(int N, int M, int Q, # <<<<<<<<<<<<<< + * + * def lengthscale_grads_in_c(int N, int M, int Q, # <<<<<<<<<<<<<< * np.ndarray[DTYPE_t, ndim=2] _tmp, * np.ndarray[DTYPE_t, ndim=2] _X, */ @@ -1638,7 +2677,7 @@ static PyObject 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*/ + __pyx_r = Py_None; __Pyx_INCREF(Py_None); + __PYX_XDEC_MEMVIEW(&__pyx_v_tmp, 1); + __PYX_XDEC_MEMVIEW(&__pyx_v_X, 1); + __PYX_XDEC_MEMVIEW(&__pyx_v_X2, 1); + __PYX_XDEC_MEMVIEW(&__pyx_v_grad, 1); + __Pyx_XGIVEREF(__pyx_r); + __Pyx_RefNannyFinishContext(); + return __pyx_r; +} + +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":194 * # experimental exception made for __getbuffer__ and __releasebuffer__ * # -- the details of this may change. * def __getbuffer__(ndarray self, Py_buffer* info, int flags): # <<<<<<<<<<<<<< @@ -1702,7 +2969,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __Pyx_GIVEREF(__pyx_v_info->obj); } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":200 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":200 * # of flags * * if info == NULL: return # <<<<<<<<<<<<<< @@ -1715,7 +2982,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P goto __pyx_L0; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":203 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":203 * * cdef int copy_shape, i, ndim * cdef int endian_detector = 1 # <<<<<<<<<<<<<< @@ -1724,7 +2991,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_endian_detector = 1; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":204 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":204 * cdef int copy_shape, i, ndim * cdef int endian_detector = 1 * cdef bint little_endian = ((&endian_detector)[0] != 0) # <<<<<<<<<<<<<< @@ -1733,7 +3000,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_little_endian = ((((char *)(&__pyx_v_endian_detector))[0]) != 0); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":206 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":206 * cdef bint little_endian = ((&endian_detector)[0] != 0) * * ndim = PyArray_NDIM(self) # <<<<<<<<<<<<<< @@ -1742,7 +3009,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_ndim = PyArray_NDIM(__pyx_v_self); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":208 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":208 * ndim = PyArray_NDIM(self) * * if sizeof(npy_intp) != sizeof(Py_ssize_t): # <<<<<<<<<<<<<< @@ -1752,7 +3019,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_1 = (((sizeof(npy_intp)) != (sizeof(Py_ssize_t))) != 0); if (__pyx_t_1) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":209 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":209 * * if sizeof(npy_intp) != sizeof(Py_ssize_t): * copy_shape = 1 # <<<<<<<<<<<<<< @@ -1764,7 +3031,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } /*else*/ { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":211 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":211 * copy_shape = 1 * else: * copy_shape = 0 # <<<<<<<<<<<<<< @@ -1775,7 +3042,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } __pyx_L4:; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":213 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":213 * copy_shape = 0 * * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) # <<<<<<<<<<<<<< @@ -1791,7 +3058,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } __pyx_L7_next_and:; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":214 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":214 * * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): # <<<<<<<<<<<<<< @@ -1803,7 +3070,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_L6_bool_binop_done:; if (__pyx_t_1) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":215 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":215 * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): * raise ValueError(u"ndarray is not C contiguous") # <<<<<<<<<<<<<< @@ -1817,7 +3084,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P {__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":217 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":217 * raise ValueError(u"ndarray is not C contiguous") * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) # <<<<<<<<<<<<<< @@ -1833,7 +3100,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } __pyx_L10_next_and:; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":218 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":218 * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): # <<<<<<<<<<<<<< @@ -1845,7 +3112,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_L9_bool_binop_done:; if (__pyx_t_1) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":219 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":219 * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): * raise ValueError(u"ndarray is not Fortran contiguous") # <<<<<<<<<<<<<< @@ -1859,7 +3126,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P {__pyx_filename = __pyx_f[1]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":221 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":221 * raise ValueError(u"ndarray is not Fortran contiguous") * * info.buf = PyArray_DATA(self) # <<<<<<<<<<<<<< @@ -1868,7 +3135,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->buf = PyArray_DATA(__pyx_v_self); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":222 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":222 * * info.buf = PyArray_DATA(self) * info.ndim = ndim # <<<<<<<<<<<<<< @@ -1877,7 +3144,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->ndim = __pyx_v_ndim; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":223 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":223 * info.buf = PyArray_DATA(self) * info.ndim = ndim * if copy_shape: # <<<<<<<<<<<<<< @@ -1887,7 +3154,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_1 = (__pyx_v_copy_shape != 0); if (__pyx_t_1) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":226 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":226 * # Allocate new buffer for strides and shape info. * # This is allocated as one block, strides first. * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) # <<<<<<<<<<<<<< @@ -1896,7 +3163,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->strides = ((Py_ssize_t *)malloc((((sizeof(Py_ssize_t)) * ((size_t)__pyx_v_ndim)) * 2))); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":227 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":227 * # This is allocated as one block, strides first. * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) * info.shape = info.strides + ndim # <<<<<<<<<<<<<< @@ -1905,7 +3172,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->shape = (__pyx_v_info->strides + __pyx_v_ndim); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":228 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":228 * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) * info.shape = info.strides + ndim * for i in range(ndim): # <<<<<<<<<<<<<< @@ -1916,7 +3183,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":229 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":229 * info.shape = info.strides + ndim * for i in range(ndim): * info.strides[i] = PyArray_STRIDES(self)[i] # <<<<<<<<<<<<<< @@ -1925,7 +3192,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ (__pyx_v_info->strides[__pyx_v_i]) = (PyArray_STRIDES(__pyx_v_self)[__pyx_v_i]); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":230 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":230 * for i in range(ndim): * info.strides[i] = PyArray_STRIDES(self)[i] * info.shape[i] = PyArray_DIMS(self)[i] # <<<<<<<<<<<<<< @@ -1938,7 +3205,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } /*else*/ { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":232 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":232 * info.shape[i] = PyArray_DIMS(self)[i] * else: * info.strides = PyArray_STRIDES(self) # <<<<<<<<<<<<<< @@ -1947,7 +3214,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->strides = ((Py_ssize_t *)PyArray_STRIDES(__pyx_v_self)); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":233 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":233 * else: * info.strides = PyArray_STRIDES(self) * info.shape = PyArray_DIMS(self) # <<<<<<<<<<<<<< @@ -1958,7 +3225,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } __pyx_L11:; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":234 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":234 * info.strides = PyArray_STRIDES(self) * info.shape = PyArray_DIMS(self) * info.suboffsets = NULL # <<<<<<<<<<<<<< @@ -1967,7 +3234,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->suboffsets = NULL; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":235 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":235 * info.shape = PyArray_DIMS(self) * info.suboffsets = NULL * info.itemsize = PyArray_ITEMSIZE(self) # <<<<<<<<<<<<<< @@ -1976,7 +3243,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->itemsize = PyArray_ITEMSIZE(__pyx_v_self); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":236 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":236 * info.suboffsets = NULL * info.itemsize = PyArray_ITEMSIZE(self) * info.readonly = not PyArray_ISWRITEABLE(self) # <<<<<<<<<<<<<< @@ -1985,7 +3252,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->readonly = (!(PyArray_ISWRITEABLE(__pyx_v_self) != 0)); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":239 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":239 * * cdef int t * cdef char* f = NULL # <<<<<<<<<<<<<< @@ -1994,7 +3261,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_f = NULL; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":240 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":240 * cdef int t * cdef char* f = NULL * cdef dtype descr = self.descr # <<<<<<<<<<<<<< @@ -2006,7 +3273,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_descr = ((PyArray_Descr *)__pyx_t_3); __pyx_t_3 = 0; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":244 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":244 * cdef int offset * * cdef bint hasfields = PyDataType_HASFIELDS(descr) # <<<<<<<<<<<<<< @@ -2015,7 +3282,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_hasfields = PyDataType_HASFIELDS(__pyx_v_descr); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":246 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":246 * cdef bint hasfields = PyDataType_HASFIELDS(descr) * * if not hasfields and not copy_shape: # <<<<<<<<<<<<<< @@ -2035,7 +3302,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_L15_bool_binop_done:; if (__pyx_t_1) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":248 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":248 * if not hasfields and not copy_shape: * # do not call releasebuffer * info.obj = None # <<<<<<<<<<<<<< @@ -2051,7 +3318,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } /*else*/ { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":251 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":251 * else: * # need to call releasebuffer * info.obj = self # <<<<<<<<<<<<<< @@ -2066,7 +3333,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } __pyx_L14:; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":253 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":253 * info.obj = self * * if not hasfields: # <<<<<<<<<<<<<< @@ -2076,7 +3343,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_1 = ((!(__pyx_v_hasfields != 0)) != 0); if (__pyx_t_1) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":254 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":254 * * if not hasfields: * t = descr.type_num # <<<<<<<<<<<<<< @@ -2086,7 +3353,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_4 = __pyx_v_descr->type_num; __pyx_v_t = __pyx_t_4; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":255 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":255 * if not hasfields: * t = descr.type_num * if ((descr.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<< @@ -2109,7 +3376,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } __pyx_L20_next_or:; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":256 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":256 * t = descr.type_num * if ((descr.byteorder == c'>' and little_endian) or * (descr.byteorder == c'<' and not little_endian)): # <<<<<<<<<<<<<< @@ -2129,7 +3396,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_L19_bool_binop_done:; if (__pyx_t_1) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 * if ((descr.byteorder == c'>' and little_endian) or * (descr.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<< @@ -2143,7 +3410,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P {__pyx_filename = __pyx_f[1]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274 * elif t == NPY_CDOUBLE: f = "Zd" * elif t == NPY_CLONGDOUBLE: f = "Zg" * elif t == NPY_OBJECT: f = "O" # <<<<<<<<<<<<<< @@ -2152,7 +3419,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ switch (__pyx_v_t) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":258 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":258 * (descr.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") * if t == NPY_BYTE: f = "b" # <<<<<<<<<<<<<< @@ -2163,7 +3430,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_b; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":259 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":259 * raise ValueError(u"Non-native byte order not supported") * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" # <<<<<<<<<<<<<< @@ -2174,7 +3441,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_B; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":260 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":260 * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" * elif t == NPY_SHORT: f = "h" # <<<<<<<<<<<<<< @@ -2185,7 +3452,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_h; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":261 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":261 * elif t == NPY_UBYTE: f = "B" * elif t == NPY_SHORT: f = "h" * elif t == NPY_USHORT: f = "H" # <<<<<<<<<<<<<< @@ -2196,7 +3463,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_H; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":262 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":262 * elif t == NPY_SHORT: f = "h" * elif t == NPY_USHORT: f = "H" * elif t == NPY_INT: f = "i" # <<<<<<<<<<<<<< @@ -2207,7 +3474,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_i; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":263 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":263 * elif t == NPY_USHORT: f = "H" * elif t == NPY_INT: f = "i" * elif t == NPY_UINT: f = "I" # <<<<<<<<<<<<<< @@ -2218,7 +3485,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_I; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":264 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":264 * elif t == NPY_INT: f = "i" * elif t == NPY_UINT: f = "I" * elif t == NPY_LONG: f = "l" # <<<<<<<<<<<<<< @@ -2229,7 +3496,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_l; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":265 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":265 * elif t == NPY_UINT: f = "I" * elif t == NPY_LONG: f = "l" * elif t == NPY_ULONG: f = "L" # <<<<<<<<<<<<<< @@ -2240,7 +3507,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_L; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":266 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":266 * elif t == NPY_LONG: f = "l" * elif t == NPY_ULONG: f = "L" * elif t == NPY_LONGLONG: f = "q" # <<<<<<<<<<<<<< @@ -2251,7 +3518,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_q; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":267 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":267 * elif t == NPY_ULONG: f = "L" * elif t == NPY_LONGLONG: f = "q" * elif t == NPY_ULONGLONG: f = "Q" # <<<<<<<<<<<<<< @@ -2262,7 +3529,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Q; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":268 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":268 * elif t == NPY_LONGLONG: f = "q" * elif t == NPY_ULONGLONG: f = "Q" * elif t == NPY_FLOAT: f = "f" # <<<<<<<<<<<<<< @@ -2273,7 +3540,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_f; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":269 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":269 * elif t == NPY_ULONGLONG: f = "Q" * elif t == NPY_FLOAT: f = "f" * elif t == NPY_DOUBLE: f = "d" # <<<<<<<<<<<<<< @@ -2284,7 +3551,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_d; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":270 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":270 * elif t == NPY_FLOAT: f = "f" * elif t == NPY_DOUBLE: f = "d" * elif t == NPY_LONGDOUBLE: f = "g" # <<<<<<<<<<<<<< @@ -2295,7 +3562,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_g; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":271 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":271 * elif t == NPY_DOUBLE: f = "d" * elif t == NPY_LONGDOUBLE: f = "g" * elif t == NPY_CFLOAT: f = "Zf" # <<<<<<<<<<<<<< @@ -2306,7 +3573,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zf; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":272 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":272 * elif t == NPY_LONGDOUBLE: f = "g" * elif t == NPY_CFLOAT: f = "Zf" * elif t == NPY_CDOUBLE: f = "Zd" # <<<<<<<<<<<<<< @@ -2317,7 +3584,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zd; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":273 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":273 * elif t == NPY_CFLOAT: f = "Zf" * elif t == NPY_CDOUBLE: f = "Zd" * elif t == NPY_CLONGDOUBLE: f = "Zg" # <<<<<<<<<<<<<< @@ -2328,7 +3595,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_v_f = __pyx_k_Zg; break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274 * elif t == NPY_CDOUBLE: f = "Zd" * elif t == NPY_CLONGDOUBLE: f = "Zg" * elif t == NPY_OBJECT: f = "O" # <<<<<<<<<<<<<< @@ -2340,7 +3607,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P break; default: - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":276 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":276 * elif t == NPY_OBJECT: f = "O" * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) # <<<<<<<<<<<<<< @@ -2366,7 +3633,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P break; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":277 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":277 * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) * info.format = f # <<<<<<<<<<<<<< @@ -2375,7 +3642,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->format = __pyx_v_f; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":278 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":278 * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) * info.format = f * return # <<<<<<<<<<<<<< @@ -2387,7 +3654,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P } /*else*/ { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":280 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":280 * return * else: * info.format = stdlib.malloc(_buffer_format_string_len) # <<<<<<<<<<<<<< @@ -2396,7 +3663,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_info->format = ((char *)malloc(255)); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":281 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":281 * else: * info.format = stdlib.malloc(_buffer_format_string_len) * info.format[0] = c'^' # Native data types, manual alignment # <<<<<<<<<<<<<< @@ -2405,7 +3672,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ (__pyx_v_info->format[0]) = '^'; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":282 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":282 * info.format = stdlib.malloc(_buffer_format_string_len) * info.format[0] = c'^' # Native data types, manual alignment * offset = 0 # <<<<<<<<<<<<<< @@ -2414,7 +3681,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P */ __pyx_v_offset = 0; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":283 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":283 * info.format[0] = c'^' # Native data types, manual alignment * offset = 0 * f = _util_dtypestring(descr, info.format + 1, # <<<<<<<<<<<<<< @@ -2424,7 +3691,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P __pyx_t_7 = __pyx_f_5numpy__util_dtypestring(__pyx_v_descr, (__pyx_v_info->format + 1), (__pyx_v_info->format + 255), (&__pyx_v_offset)); if (unlikely(__pyx_t_7 == NULL)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 283; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_v_f = __pyx_t_7; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":286 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":286 * info.format + _buffer_format_string_len, * &offset) * f[0] = c'\0' # Terminate format string # <<<<<<<<<<<<<< @@ -2434,7 +3701,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P (__pyx_v_f[0]) = '\x00'; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":194 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":194 * # experimental exception made for __getbuffer__ and __releasebuffer__ * # -- the details of this may change. * def __getbuffer__(ndarray self, Py_buffer* info, int flags): # <<<<<<<<<<<<<< @@ -2466,7 +3733,7 @@ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, P return __pyx_r; } -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":288 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":288 * f[0] = c'\0' # Terminate format string * * def __releasebuffer__(ndarray self, Py_buffer* info): # <<<<<<<<<<<<<< @@ -2490,7 +3757,7 @@ static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_s int __pyx_t_1; __Pyx_RefNannySetupContext("__releasebuffer__", 0); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":289 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":289 * * def __releasebuffer__(ndarray self, Py_buffer* info): * if PyArray_HASFIELDS(self): # <<<<<<<<<<<<<< @@ -2500,7 +3767,7 @@ static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_s __pyx_t_1 = (PyArray_HASFIELDS(__pyx_v_self) != 0); if (__pyx_t_1) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":290 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":290 * def __releasebuffer__(ndarray self, Py_buffer* info): * if PyArray_HASFIELDS(self): * stdlib.free(info.format) # <<<<<<<<<<<<<< @@ -2512,7 +3779,7 @@ static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_s } __pyx_L3:; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":291 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":291 * if PyArray_HASFIELDS(self): * stdlib.free(info.format) * if sizeof(npy_intp) != sizeof(Py_ssize_t): # <<<<<<<<<<<<<< @@ -2522,7 +3789,7 @@ static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_s __pyx_t_1 = (((sizeof(npy_intp)) != (sizeof(Py_ssize_t))) != 0); if (__pyx_t_1) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":292 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":292 * stdlib.free(info.format) * if sizeof(npy_intp) != sizeof(Py_ssize_t): * stdlib.free(info.strides) # <<<<<<<<<<<<<< @@ -2534,7 +3801,7 @@ static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_s } __pyx_L4:; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":288 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":288 * f[0] = c'\0' # Terminate format string * * def __releasebuffer__(ndarray self, Py_buffer* info): # <<<<<<<<<<<<<< @@ -2546,7 +3813,7 @@ static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_s __Pyx_RefNannyFinishContext(); } -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":768 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":768 * ctypedef npy_cdouble complex_t * * cdef inline object PyArray_MultiIterNew1(a): # <<<<<<<<<<<<<< @@ -2563,7 +3830,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew1(PyObject *__ int __pyx_clineno = 0; __Pyx_RefNannySetupContext("PyArray_MultiIterNew1", 0); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":769 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":769 * * cdef inline object PyArray_MultiIterNew1(a): * return PyArray_MultiIterNew(1, a) # <<<<<<<<<<<<<< @@ -2577,7 +3844,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew1(PyObject *__ __pyx_t_1 = 0; goto __pyx_L0; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":768 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":768 * ctypedef npy_cdouble complex_t * * cdef inline object PyArray_MultiIterNew1(a): # <<<<<<<<<<<<<< @@ -2596,7 +3863,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew1(PyObject *__ return __pyx_r; } -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":771 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":771 * return PyArray_MultiIterNew(1, a) * * cdef inline object PyArray_MultiIterNew2(a, b): # <<<<<<<<<<<<<< @@ -2613,7 +3880,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew2(PyObject *__ int __pyx_clineno = 0; __Pyx_RefNannySetupContext("PyArray_MultiIterNew2", 0); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":772 + /* 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CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew3(PyObject *__ return __pyx_r; } -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":777 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":777 * return PyArray_MultiIterNew(3, a, b, c) * * cdef inline object PyArray_MultiIterNew4(a, b, c, d): # <<<<<<<<<<<<<< @@ -2713,7 +3980,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew4(PyObject *__ int __pyx_clineno = 0; __Pyx_RefNannySetupContext("PyArray_MultiIterNew4", 0); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":778 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":778 * * cdef inline object PyArray_MultiIterNew4(a, b, c, d): * return PyArray_MultiIterNew(4, a, b, c, d) # <<<<<<<<<<<<<< @@ -2727,7 +3994,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew4(PyObject *__ __pyx_t_1 = 0; goto __pyx_L0; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":777 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":777 * return PyArray_MultiIterNew(3, a, b, c) * * cdef inline object PyArray_MultiIterNew4(a, b, c, d): # <<<<<<<<<<<<<< @@ -2746,7 +4013,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew4(PyObject *__ return __pyx_r; } -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":780 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":780 * return PyArray_MultiIterNew(4, a, b, c, d) * * cdef inline object PyArray_MultiIterNew5(a, b, c, d, e): # <<<<<<<<<<<<<< @@ -2763,7 +4030,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew5(PyObject *__ int __pyx_clineno = 0; __Pyx_RefNannySetupContext("PyArray_MultiIterNew5", 0); - /* 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"../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":795 * * for childname in descr.names: * fields = descr.fields[childname] # <<<<<<<<<<<<<< @@ -2881,7 +4148,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_XDECREF_SET(__pyx_v_fields, ((PyObject*)__pyx_t_3)); __pyx_t_3 = 0; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":796 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":796 * for childname in descr.names: * fields = descr.fields[childname] * child, new_offset = fields # <<<<<<<<<<<<<< @@ -2920,7 +4187,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_XDECREF_SET(__pyx_v_new_offset, __pyx_t_4); __pyx_t_4 = 0; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":798 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":798 * child, new_offset = fields * * if (end - f) - (new_offset - offset[0]) < 15: # <<<<<<<<<<<<<< @@ -2937,7 +4204,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __pyx_t_6 = ((((__pyx_v_end - __pyx_v_f) - ((int)__pyx_t_5)) < 15) != 0); if (__pyx_t_6) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":799 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":799 * * if (end - f) - (new_offset - offset[0]) < 15: * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") # <<<<<<<<<<<<<< @@ -2951,7 +4218,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx {__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - /* 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"../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":803 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":803 * if ((child.byteorder == c'>' and little_endian) or * (child.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<< @@ -3008,7 +4275,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx {__pyx_filename = __pyx_f[1]; __pyx_lineno = 803; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":813 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":813 * * # Output padding bytes * while offset[0] < new_offset: # <<<<<<<<<<<<<< @@ -3024,7 +4291,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; if (!__pyx_t_6) break; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":814 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":814 * # Output padding bytes * while offset[0] < new_offset: * f[0] = 120 # "x"; pad byte # <<<<<<<<<<<<<< @@ -3033,7 +4300,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx */ (__pyx_v_f[0]) = 120; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":815 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":815 * while offset[0] < new_offset: * f[0] = 120 # "x"; pad byte * f += 1 # <<<<<<<<<<<<<< @@ -3042,7 +4309,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx */ __pyx_v_f = (__pyx_v_f + 1); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":816 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":816 * f[0] = 120 # "x"; pad byte * f += 1 * offset[0] += 1 # <<<<<<<<<<<<<< @@ -3053,7 +4320,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx (__pyx_v_offset[__pyx_t_8]) = ((__pyx_v_offset[__pyx_t_8]) + 1); } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":818 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":818 * offset[0] += 1 * * offset[0] += child.itemsize # <<<<<<<<<<<<<< @@ -3063,7 +4330,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __pyx_t_8 = 0; (__pyx_v_offset[__pyx_t_8]) = ((__pyx_v_offset[__pyx_t_8]) + __pyx_v_child->elsize); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":820 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":820 * offset[0] += 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CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __pyx_t_6 = (((__pyx_v_end - __pyx_v_f) < 5) != 0); if (__pyx_t_6) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":823 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":823 * t = child.type_num * if end - f < 5: * raise RuntimeError(u"Format string allocated too short.") # <<<<<<<<<<<<<< @@ -3109,7 +4376,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx {__pyx_filename = __pyx_f[1]; __pyx_lineno = 823; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":826 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":826 * * # Until ticket #99 is fixed, use integers to avoid warnings * if t == NPY_BYTE: f[0] = 98 #"b" # <<<<<<<<<<<<<< @@ -3127,7 +4394,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":827 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":827 * # Until ticket #99 is fixed, use integers to avoid warnings * if t == NPY_BYTE: f[0] = 98 #"b" * elif t == NPY_UBYTE: f[0] = 66 #"B" # <<<<<<<<<<<<<< @@ -3145,7 +4412,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":828 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":828 * if t == NPY_BYTE: f[0] = 98 #"b" * elif t == NPY_UBYTE: f[0] = 66 #"B" * elif t == NPY_SHORT: f[0] = 104 #"h" # <<<<<<<<<<<<<< @@ -3163,7 +4430,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":829 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":829 * elif t == NPY_UBYTE: f[0] = 66 #"B" * elif t == NPY_SHORT: f[0] = 104 #"h" * elif t == NPY_USHORT: f[0] = 72 #"H" # <<<<<<<<<<<<<< @@ -3181,7 +4448,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":830 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":830 * elif t == NPY_SHORT: f[0] = 104 #"h" * elif t == NPY_USHORT: f[0] = 72 #"H" * elif t == NPY_INT: f[0] = 105 #"i" # <<<<<<<<<<<<<< @@ -3199,7 +4466,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":831 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":831 * elif t == NPY_USHORT: f[0] = 72 #"H" * elif t == NPY_INT: f[0] = 105 #"i" * elif t == NPY_UINT: f[0] = 73 #"I" # <<<<<<<<<<<<<< @@ -3217,7 +4484,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":832 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":832 * elif t == NPY_INT: f[0] = 105 #"i" * elif t == NPY_UINT: f[0] = 73 #"I" * elif t == NPY_LONG: f[0] = 108 #"l" # <<<<<<<<<<<<<< @@ -3235,7 +4502,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":833 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":833 * elif t == NPY_UINT: f[0] = 73 #"I" * elif t == NPY_LONG: f[0] = 108 #"l" * elif t == NPY_ULONG: f[0] = 76 #"L" # <<<<<<<<<<<<<< @@ -3253,7 +4520,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":834 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":834 * elif t == NPY_LONG: f[0] = 108 #"l" * elif t == NPY_ULONG: f[0] = 76 #"L" * elif t == NPY_LONGLONG: f[0] = 113 #"q" # <<<<<<<<<<<<<< @@ -3271,7 +4538,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":835 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":835 * elif t == NPY_ULONG: f[0] = 76 #"L" * elif t == NPY_LONGLONG: f[0] = 113 #"q" * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" # <<<<<<<<<<<<<< @@ -3289,7 +4556,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":836 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":836 * elif t == NPY_LONGLONG: f[0] = 113 #"q" * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" * elif t == NPY_FLOAT: f[0] = 102 #"f" # <<<<<<<<<<<<<< @@ -3307,7 +4574,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":837 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":837 * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" * elif t == NPY_FLOAT: f[0] = 102 #"f" * elif t == NPY_DOUBLE: f[0] = 100 #"d" # <<<<<<<<<<<<<< @@ -3325,7 +4592,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":838 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":838 * elif t == NPY_FLOAT: f[0] = 102 #"f" * elif t == NPY_DOUBLE: f[0] = 100 #"d" * elif t == NPY_LONGDOUBLE: f[0] = 103 #"g" # <<<<<<<<<<<<<< @@ -3343,7 +4610,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":839 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":839 * elif t == NPY_DOUBLE: f[0] = 100 #"d" * elif t == NPY_LONGDOUBLE: f[0] = 103 #"g" * elif t == NPY_CFLOAT: f[0] = 90; f[1] = 102; f += 1 # Zf # <<<<<<<<<<<<<< @@ -3363,7 +4630,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":840 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":840 * elif t == NPY_LONGDOUBLE: f[0] = 103 #"g" * elif t == NPY_CFLOAT: f[0] = 90; f[1] = 102; f += 1 # Zf * elif t == NPY_CDOUBLE: f[0] = 90; f[1] = 100; f += 1 # Zd # <<<<<<<<<<<<<< @@ -3383,7 +4650,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":841 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":841 * elif t == NPY_CFLOAT: f[0] = 90; f[1] = 102; f += 1 # Zf * elif t == NPY_CDOUBLE: f[0] = 90; f[1] = 100; f += 1 # Zd * elif t == NPY_CLONGDOUBLE: f[0] = 90; f[1] = 103; f += 1 # Zg # <<<<<<<<<<<<<< @@ -3403,7 +4670,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx goto __pyx_L15; } - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":842 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":842 * elif t == NPY_CDOUBLE: f[0] = 90; f[1] = 100; f += 1 # Zd * elif t == NPY_CLONGDOUBLE: f[0] = 90; f[1] = 103; f += 1 # Zg * elif t == NPY_OBJECT: f[0] = 79 #"O" # <<<<<<<<<<<<<< @@ -3422,7 +4689,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx } /*else*/ { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":844 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":844 * elif t == NPY_OBJECT: f[0] = 79 #"O" * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) # <<<<<<<<<<<<<< @@ -3445,7 +4712,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx } __pyx_L15:; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":845 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":845 * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) * f += 1 # <<<<<<<<<<<<<< @@ -3457,7 +4724,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx } /*else*/ { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":849 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":849 * # Cython ignores struct boundary information ("T{...}"), * # so don't output it * f = _util_dtypestring(child, f, end, offset) # <<<<<<<<<<<<<< @@ -3469,7 +4736,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx } __pyx_L13:; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":794 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":794 * cdef tuple fields * * for childname in descr.names: # <<<<<<<<<<<<<< @@ -3479,7 +4746,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx } __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":850 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":850 * # so don't output it * f = _util_dtypestring(child, f, end, offset) * return f # <<<<<<<<<<<<<< @@ -3489,7 +4756,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx __pyx_r = __pyx_v_f; goto __pyx_L0; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":783 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":783 * return PyArray_MultiIterNew(5, a, b, c, d, e) * * cdef inline char* _util_dtypestring(dtype descr, char* f, char* end, int* offset) except NULL: # <<<<<<<<<<<<<< @@ -3514,7 +4781,7 @@ static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx return __pyx_r; } -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":966 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":966 * * * cdef inline void set_array_base(ndarray arr, object base): # <<<<<<<<<<<<<< @@ -3529,7 +4796,7 @@ static CYTHON_INLINE void __pyx_f_5numpy_set_array_base(PyArrayObject *__pyx_v_a int __pyx_t_2; __Pyx_RefNannySetupContext("set_array_base", 0); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":968 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":968 * cdef inline void set_array_base(ndarray arr, object base): * cdef PyObject* baseptr * if base is None: # <<<<<<<<<<<<<< @@ -3540,7 +4807,7 @@ static CYTHON_INLINE void __pyx_f_5numpy_set_array_base(PyArrayObject *__pyx_v_a __pyx_t_2 = (__pyx_t_1 != 0); if (__pyx_t_2) { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":969 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":969 * cdef PyObject* baseptr * if base is None: * baseptr = NULL # <<<<<<<<<<<<<< @@ -3552,7 +4819,7 @@ static CYTHON_INLINE void __pyx_f_5numpy_set_array_base(PyArrayObject *__pyx_v_a } /*else*/ { - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":971 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":971 * baseptr = NULL * else: * Py_INCREF(base) # important to do this before decref below! # <<<<<<<<<<<<<< @@ -3561,7 +4828,7 @@ static CYTHON_INLINE void __pyx_f_5numpy_set_array_base(PyArrayObject *__pyx_v_a */ Py_INCREF(__pyx_v_base); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":972 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":972 * else: * Py_INCREF(base) # important to do this before decref below! * baseptr = base # <<<<<<<<<<<<<< @@ -3572,7 +4839,7 @@ static CYTHON_INLINE void __pyx_f_5numpy_set_array_base(PyArrayObject *__pyx_v_a } __pyx_L3:; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":973 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":973 * Py_INCREF(base) # important to do this before decref below! * baseptr = base * Py_XDECREF(arr.base) # <<<<<<<<<<<<<< @@ -3581,7 +4848,7 @@ static CYTHON_INLINE void __pyx_f_5numpy_set_array_base(PyArrayObject *__pyx_v_a */ Py_XDECREF(__pyx_v_arr->base); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":974 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":974 * baseptr = base * Py_XDECREF(arr.base) * arr.base = baseptr # <<<<<<<<<<<<<< @@ -3590,7 +4857,7 @@ static CYTHON_INLINE void __pyx_f_5numpy_set_array_base(PyArrayObject *__pyx_v_a */ __pyx_v_arr->base = __pyx_v_baseptr; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":966 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":966 * * * cdef inline void set_array_base(ndarray arr, object base): # <<<<<<<<<<<<<< @@ -3602,7 +4869,7 @@ static CYTHON_INLINE void __pyx_f_5numpy_set_array_base(PyArrayObject *__pyx_v_a __Pyx_RefNannyFinishContext(); } -/* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":976 +/* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":976 * arr.base = baseptr * * cdef inline object get_array_base(ndarray arr): # <<<<<<<<<<<<<< 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mode="c", bint allocate_buffer=True): + * + */ + +/* Python wrapper */ +static int __pyx_array___cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static int __pyx_array___cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + PyObject *__pyx_v_shape = 0; + Py_ssize_t __pyx_v_itemsize; + PyObject *__pyx_v_format = 0; + PyObject *__pyx_v_mode = 0; + int __pyx_v_allocate_buffer; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; + int __pyx_r; + __Pyx_RefNannyDeclarations + __Pyx_RefNannySetupContext("__cinit__ (wrapper)", 0); + { + static PyObject **__pyx_pyargnames[] = {&__pyx_n_s_shape,&__pyx_n_s_itemsize,&__pyx_n_s_format,&__pyx_n_s_mode,&__pyx_n_s_allocate_buffer,0}; + PyObject* values[5] = {0,0,0,0,0}; + values[3] = ((PyObject *)__pyx_n_s_c); + if (unlikely(__pyx_kwds)) { + Py_ssize_t kw_args; + const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args); + switch (pos_args) { + case 5: 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__Pyx_XDECREF(__pyx_t_9); + __Pyx_AddTraceback("View.MemoryView.memview_slice", __pyx_clineno, __pyx_lineno, __pyx_filename); + __pyx_r = 0; + __pyx_L0:; + __Pyx_XDECREF((PyObject *)__pyx_v_memviewsliceobj); + __Pyx_XDECREF(__pyx_v_index); + __Pyx_XGIVEREF((PyObject *)__pyx_r); + __Pyx_RefNannyFinishContext(); + return __pyx_r; +} + +/* "View.MemoryView":764 + * + * @cname('__pyx_memoryview_slice_memviewslice') + * cdef int slice_memviewslice( # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * Py_ssize_t shape, Py_ssize_t stride, Py_ssize_t suboffset, + */ + +static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, Py_ssize_t __pyx_v_shape, Py_ssize_t __pyx_v_stride, Py_ssize_t __pyx_v_suboffset, int __pyx_v_dim, int __pyx_v_new_ndim, int *__pyx_v_suboffset_dim, Py_ssize_t __pyx_v_start, Py_ssize_t __pyx_v_stop, Py_ssize_t __pyx_v_step, int __pyx_v_have_start, int __pyx_v_have_stop, int __pyx_v_have_step, int __pyx_v_is_slice) { + Py_ssize_t __pyx_v_new_shape; + 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of bounds (axis %d)", dim) + * else: + */ + __pyx_t_1 = (0 <= __pyx_v_start); + if (__pyx_t_1) { + __pyx_t_1 = (__pyx_v_start < __pyx_v_shape); + } + __pyx_t_2 = ((!(__pyx_t_1 != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":789 + * start += shape + * if not 0 <= start < shape: + * _err_dim(IndexError, "Index out of bounds (axis %d)", dim) # <<<<<<<<<<<<<< + * else: + * + */ + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, __pyx_k_Index_out_of_bounds_axis_d, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 789; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + goto __pyx_L5; + } + __pyx_L5:; + goto __pyx_L3; + } + /*else*/ { + + /* "View.MemoryView":792 + * else: + * + * negative_step = have_step != 0 and step < 0 # <<<<<<<<<<<<<< + * + * if have_step and step == 0: + */ + __pyx_t_1 = ((__pyx_v_have_step != 0) != 0); + if (__pyx_t_1) { + goto __pyx_L7_next_and; + } else { + __pyx_t_2 = __pyx_t_1; + goto __pyx_L6_bool_binop_done; + } + __pyx_L7_next_and:; + __pyx_t_1 = ((__pyx_v_step < 0) != 0); + __pyx_t_2 = __pyx_t_1; + __pyx_L6_bool_binop_done:; + __pyx_v_negative_step = __pyx_t_2; + + /* "View.MemoryView":794 + * negative_step = have_step != 0 and step < 0 + * + * if have_step and step == 0: # <<<<<<<<<<<<<< + * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) + * + */ + __pyx_t_1 = (__pyx_v_have_step != 0); + if (__pyx_t_1) { + goto __pyx_L10_next_and; + } else { + __pyx_t_2 = __pyx_t_1; + goto __pyx_L9_bool_binop_done; + } + __pyx_L10_next_and:; + __pyx_t_1 = ((__pyx_v_step == 0) != 0); + __pyx_t_2 = __pyx_t_1; + __pyx_L9_bool_binop_done:; + if (__pyx_t_2) { + + /* "View.MemoryView":795 + * + * if have_step and step == 0: + * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, __pyx_k_Step_may_not_be_zero_axis_d, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + goto __pyx_L8; + } + __pyx_L8:; + + /* "View.MemoryView":798 + * + * + * if have_start: # <<<<<<<<<<<<<< + * if start < 0: + * start += shape + */ + __pyx_t_2 = (__pyx_v_have_start != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":799 + * + * if have_start: + * if start < 0: # <<<<<<<<<<<<<< + * start += shape + * if start < 0: + */ + __pyx_t_2 = ((__pyx_v_start < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":800 + * if have_start: + * if start < 0: + * start += shape # <<<<<<<<<<<<<< + * if start < 0: + * start = 0 + */ + __pyx_v_start = (__pyx_v_start + __pyx_v_shape); + + /* "View.MemoryView":801 + * if start < 0: + * start += shape + * if start < 0: # <<<<<<<<<<<<<< + * start = 0 + * elif start >= shape: + */ + __pyx_t_2 = ((__pyx_v_start < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":802 + * start += shape + * if start < 0: + * start = 0 # <<<<<<<<<<<<<< + * elif start >= shape: + * if negative_step: + */ + __pyx_v_start = 0; + goto __pyx_L13; + } + __pyx_L13:; + goto __pyx_L12; + } + + /* "View.MemoryView":803 + * if start < 0: + * start = 0 + * elif start >= shape: # <<<<<<<<<<<<<< + * if negative_step: + * start = shape - 1 + */ + __pyx_t_2 = ((__pyx_v_start >= __pyx_v_shape) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":804 + * start = 0 + * elif start >= shape: + * if negative_step: # <<<<<<<<<<<<<< + * start = shape - 1 + * else: + */ + __pyx_t_2 = (__pyx_v_negative_step != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":805 + * elif start >= shape: + * if negative_step: + * start = shape - 1 # <<<<<<<<<<<<<< + * else: + * start = shape + */ + __pyx_v_start = (__pyx_v_shape - 1); + goto __pyx_L14; + } + /*else*/ { + + /* "View.MemoryView":807 + * start = shape - 1 + * else: + * start = shape # <<<<<<<<<<<<<< + * else: + * if negative_step: + */ + __pyx_v_start = __pyx_v_shape; + } + __pyx_L14:; + goto __pyx_L12; + } + __pyx_L12:; + goto __pyx_L11; + } + /*else*/ { + + /* "View.MemoryView":809 + * start = shape + * else: + * if negative_step: # <<<<<<<<<<<<<< + * start = shape - 1 + * else: + */ + __pyx_t_2 = (__pyx_v_negative_step != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":810 + * else: + * if negative_step: + * start = shape - 1 # <<<<<<<<<<<<<< + * else: + * start = 0 + */ + __pyx_v_start = (__pyx_v_shape - 1); + goto __pyx_L15; + } + /*else*/ { + + /* "View.MemoryView":812 + * start = shape - 1 + * else: + * start = 0 # <<<<<<<<<<<<<< + * + * if have_stop: + */ + __pyx_v_start = 0; + } + __pyx_L15:; + } + __pyx_L11:; + + /* "View.MemoryView":814 + * start = 0 + * + * if have_stop: # <<<<<<<<<<<<<< + * if stop < 0: + * stop += shape + */ + __pyx_t_2 = (__pyx_v_have_stop != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":815 + * + * if have_stop: + * if stop < 0: # <<<<<<<<<<<<<< + * stop += shape + * if stop < 0: + */ + __pyx_t_2 = ((__pyx_v_stop < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":816 + * if have_stop: + * if stop < 0: + * stop += shape # <<<<<<<<<<<<<< + * if stop < 0: + * stop = 0 + */ + __pyx_v_stop = (__pyx_v_stop + __pyx_v_shape); + + /* "View.MemoryView":817 + * if stop < 0: + * stop += shape + * if stop < 0: # <<<<<<<<<<<<<< + * stop = 0 + * elif stop > shape: + */ + __pyx_t_2 = ((__pyx_v_stop < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":818 + * stop += shape + * if stop < 0: + * stop = 0 # <<<<<<<<<<<<<< + * elif stop > shape: + * stop = shape + */ + __pyx_v_stop = 0; + goto __pyx_L18; + } + __pyx_L18:; + goto __pyx_L17; + } + + /* "View.MemoryView":819 + * if stop < 0: + * stop = 0 + * elif stop > shape: # <<<<<<<<<<<<<< + * stop = shape + * else: + */ + __pyx_t_2 = ((__pyx_v_stop > __pyx_v_shape) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":820 + * stop = 0 + * elif stop > shape: + * stop = shape # <<<<<<<<<<<<<< + * else: + * if negative_step: + */ + __pyx_v_stop = __pyx_v_shape; + goto __pyx_L17; + } + __pyx_L17:; + goto __pyx_L16; + } + /*else*/ { + + /* "View.MemoryView":822 + * stop = shape + * else: + * if negative_step: # <<<<<<<<<<<<<< + * stop = -1 + * else: + */ + __pyx_t_2 = (__pyx_v_negative_step != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":823 + * else: + * if negative_step: + * stop = -1 # <<<<<<<<<<<<<< + * else: + * stop = shape + */ + __pyx_v_stop = -1; + goto __pyx_L19; + } + /*else*/ { + + /* "View.MemoryView":825 + * stop = -1 + * else: + * stop = shape # <<<<<<<<<<<<<< + * + * if not have_step: + */ + __pyx_v_stop = __pyx_v_shape; + } + __pyx_L19:; + } + __pyx_L16:; + + /* "View.MemoryView":827 + * stop = shape + * + * if not have_step: # <<<<<<<<<<<<<< + * step = 1 + * + */ + __pyx_t_2 = ((!(__pyx_v_have_step != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":828 + * + * if not have_step: + * step = 1 # <<<<<<<<<<<<<< + * + * + */ + __pyx_v_step = 1; + goto __pyx_L20; + } + __pyx_L20:; + + /* "View.MemoryView":832 + * + * with cython.cdivision(True): + * new_shape = (stop - start) // step # <<<<<<<<<<<<<< + * + * if (stop - start) - step * new_shape: + */ + __pyx_v_new_shape = ((__pyx_v_stop - __pyx_v_start) / __pyx_v_step); + + /* "View.MemoryView":834 + * new_shape = (stop - start) // step + * + * if (stop - start) - step * new_shape: # <<<<<<<<<<<<<< + * new_shape += 1 + * + */ + __pyx_t_2 = (((__pyx_v_stop - __pyx_v_start) - (__pyx_v_step * __pyx_v_new_shape)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":835 + * + * if (stop - start) - step * new_shape: + * new_shape += 1 # <<<<<<<<<<<<<< + * + * if new_shape < 0: + */ + __pyx_v_new_shape = (__pyx_v_new_shape + 1); + goto __pyx_L21; + } + __pyx_L21:; + + /* "View.MemoryView":837 + * new_shape += 1 + * + * if new_shape < 0: # <<<<<<<<<<<<<< + * new_shape = 0 + * + */ + __pyx_t_2 = ((__pyx_v_new_shape < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":838 + * + * if new_shape < 0: + * new_shape = 0 # <<<<<<<<<<<<<< + * + * + */ + __pyx_v_new_shape = 0; + goto __pyx_L22; + } + __pyx_L22:; + + /* "View.MemoryView":841 + * + * + * dst.strides[new_ndim] = stride * step # <<<<<<<<<<<<<< + * dst.shape[new_ndim] = new_shape + * dst.suboffsets[new_ndim] = suboffset + */ + (__pyx_v_dst->strides[__pyx_v_new_ndim]) = (__pyx_v_stride * __pyx_v_step); + + /* "View.MemoryView":842 + * + * dst.strides[new_ndim] = stride * step + * dst.shape[new_ndim] = new_shape # <<<<<<<<<<<<<< + * dst.suboffsets[new_ndim] = suboffset + * + */ + (__pyx_v_dst->shape[__pyx_v_new_ndim]) = __pyx_v_new_shape; + + /* "View.MemoryView":843 + * dst.strides[new_ndim] = stride * step + * dst.shape[new_ndim] = new_shape + * dst.suboffsets[new_ndim] = suboffset # <<<<<<<<<<<<<< + * + * + */ + (__pyx_v_dst->suboffsets[__pyx_v_new_ndim]) = __pyx_v_suboffset; + } + __pyx_L3:; + + /* "View.MemoryView":846 + * + * + * if suboffset_dim[0] < 0: # <<<<<<<<<<<<<< + * dst.data += start * stride + * else: + */ + __pyx_t_2 = (((__pyx_v_suboffset_dim[0]) < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":847 + * + * if suboffset_dim[0] < 0: + * dst.data += start * stride # <<<<<<<<<<<<<< + * else: + * dst.suboffsets[suboffset_dim[0]] += start * stride + */ + __pyx_v_dst->data = (__pyx_v_dst->data + (__pyx_v_start * __pyx_v_stride)); + goto __pyx_L23; + } + /*else*/ { + + /* "View.MemoryView":849 + * dst.data += start * stride + * else: + * dst.suboffsets[suboffset_dim[0]] += start * stride # <<<<<<<<<<<<<< + * + * if suboffset >= 0: + */ + __pyx_t_3 = (__pyx_v_suboffset_dim[0]); + (__pyx_v_dst->suboffsets[__pyx_t_3]) = ((__pyx_v_dst->suboffsets[__pyx_t_3]) + (__pyx_v_start * __pyx_v_stride)); + } + __pyx_L23:; + + /* "View.MemoryView":851 + * dst.suboffsets[suboffset_dim[0]] += start * stride + * + * if suboffset >= 0: # <<<<<<<<<<<<<< + * if not is_slice: + * if new_ndim == 0: + */ + __pyx_t_2 = ((__pyx_v_suboffset >= 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":852 + * + * if suboffset >= 0: + * if not is_slice: # <<<<<<<<<<<<<< + * if new_ndim == 0: + * dst.data = ( dst.data)[0] + suboffset + */ + __pyx_t_2 = ((!(__pyx_v_is_slice != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":853 + * if suboffset >= 0: + * if not is_slice: + * if new_ndim == 0: # <<<<<<<<<<<<<< + * dst.data = ( dst.data)[0] + suboffset + * else: + */ + __pyx_t_2 = ((__pyx_v_new_ndim == 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":854 + * if not is_slice: + * if new_ndim == 0: + * dst.data = ( dst.data)[0] + suboffset # <<<<<<<<<<<<<< + * else: + * _err_dim(IndexError, "All dimensions preceding dimension %d " + */ + __pyx_v_dst->data = ((((char **)__pyx_v_dst->data)[0]) + __pyx_v_suboffset); + goto __pyx_L26; + } + /*else*/ { + + /* "View.MemoryView":856 + * dst.data = ( dst.data)[0] + suboffset + * else: + * _err_dim(IndexError, "All dimensions preceding dimension %d " # <<<<<<<<<<<<<< + * "must be indexed and not sliced", dim) + * else: + */ + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, __pyx_k_All_dimensions_preceding_dimensi, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 856; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + } + __pyx_L26:; + goto __pyx_L25; + } + /*else*/ { + + /* "View.MemoryView":859 + * "must be indexed and not sliced", dim) + * else: + * suboffset_dim[0] = new_ndim # <<<<<<<<<<<<<< + * + * return 0 + */ + (__pyx_v_suboffset_dim[0]) = __pyx_v_new_ndim; + } + __pyx_L25:; + goto __pyx_L24; + } + __pyx_L24:; + + /* "View.MemoryView":861 + * suboffset_dim[0] = new_ndim + * + * return 0 # <<<<<<<<<<<<<< + * + * + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "View.MemoryView":764 + * + * @cname('__pyx_memoryview_slice_memviewslice') + * cdef int slice_memviewslice( # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * Py_ssize_t shape, Py_ssize_t stride, Py_ssize_t suboffset, + */ + + /* function exit code */ + __pyx_L1_error:; + { + #ifdef WITH_THREAD + PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); + #endif + __Pyx_AddTraceback("View.MemoryView.slice_memviewslice", __pyx_clineno, __pyx_lineno, __pyx_filename); + #ifdef WITH_THREAD + PyGILState_Release(__pyx_gilstate_save); + #endif + } + __pyx_r = -1; + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":867 + * + * @cname('__pyx_pybuffer_index') + * cdef char *pybuffer_index(Py_buffer *view, char *bufp, Py_ssize_t index, # <<<<<<<<<<<<<< + * Py_ssize_t dim) except NULL: + * cdef Py_ssize_t shape, stride, suboffset = -1 + */ + +static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, Py_ssize_t __pyx_v_index, Py_ssize_t __pyx_v_dim) { + Py_ssize_t __pyx_v_shape; + Py_ssize_t __pyx_v_stride; + Py_ssize_t __pyx_v_suboffset; + Py_ssize_t __pyx_v_itemsize; + char *__pyx_v_resultp; + char *__pyx_r; + __Pyx_RefNannyDeclarations + Py_ssize_t __pyx_t_1; + int __pyx_t_2; + PyObject *__pyx_t_3 = NULL; + PyObject *__pyx_t_4 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; + __Pyx_RefNannySetupContext("pybuffer_index", 0); + + /* "View.MemoryView":869 + * cdef char *pybuffer_index(Py_buffer *view, char *bufp, Py_ssize_t index, + * Py_ssize_t dim) except NULL: + * cdef Py_ssize_t shape, stride, suboffset = -1 # <<<<<<<<<<<<<< + * cdef Py_ssize_t itemsize = view.itemsize + * cdef char *resultp + */ + __pyx_v_suboffset = -1; + + /* "View.MemoryView":870 + * Py_ssize_t dim) except NULL: + * cdef Py_ssize_t shape, stride, suboffset = -1 + * cdef Py_ssize_t itemsize = view.itemsize # <<<<<<<<<<<<<< + * cdef char *resultp + * + */ + __pyx_t_1 = __pyx_v_view->itemsize; + __pyx_v_itemsize = __pyx_t_1; + + /* "View.MemoryView":873 + * cdef char *resultp + * + * if view.ndim == 0: # <<<<<<<<<<<<<< + * shape = view.len / itemsize + * stride = itemsize + */ + __pyx_t_2 = ((__pyx_v_view->ndim == 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":874 + * + * if view.ndim == 0: + * shape = view.len / itemsize # <<<<<<<<<<<<<< + * stride = itemsize + * else: + */ + if (unlikely(__pyx_v_itemsize == 0)) { + #ifdef WITH_THREAD + PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); + #endif + PyErr_SetString(PyExc_ZeroDivisionError, "integer division or modulo by zero"); + #ifdef WITH_THREAD + PyGILState_Release(__pyx_gilstate_save); + #endif + {__pyx_filename = __pyx_f[2]; __pyx_lineno = 874; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + } + else if (sizeof(Py_ssize_t) == sizeof(long) && unlikely(__pyx_v_itemsize == -1) && unlikely(UNARY_NEG_WOULD_OVERFLOW(__pyx_v_view->len))) { + #ifdef WITH_THREAD + PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); + #endif + PyErr_SetString(PyExc_OverflowError, "value too large to perform division"); + #ifdef WITH_THREAD + PyGILState_Release(__pyx_gilstate_save); + #endif + {__pyx_filename = __pyx_f[2]; __pyx_lineno = 874; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + } + __pyx_v_shape = __Pyx_div_Py_ssize_t(__pyx_v_view->len, __pyx_v_itemsize); + + /* "View.MemoryView":875 + * if view.ndim == 0: + * shape = view.len / itemsize + * stride = itemsize # <<<<<<<<<<<<<< + * else: + * shape = view.shape[dim] + */ + __pyx_v_stride = __pyx_v_itemsize; + goto __pyx_L3; + } + /*else*/ { + + /* "View.MemoryView":877 + * stride = itemsize + * else: + * shape = view.shape[dim] # <<<<<<<<<<<<<< + * stride = view.strides[dim] + * if view.suboffsets != NULL: + */ + __pyx_v_shape = (__pyx_v_view->shape[__pyx_v_dim]); + + /* "View.MemoryView":878 + * else: + * shape = view.shape[dim] + * stride = view.strides[dim] # <<<<<<<<<<<<<< + * if view.suboffsets != NULL: + * suboffset = view.suboffsets[dim] + */ + __pyx_v_stride = (__pyx_v_view->strides[__pyx_v_dim]); + + /* "View.MemoryView":879 + * shape = view.shape[dim] + * stride = view.strides[dim] + * if view.suboffsets != NULL: # <<<<<<<<<<<<<< + * suboffset = view.suboffsets[dim] + * + */ + __pyx_t_2 = ((__pyx_v_view->suboffsets != NULL) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":880 + * stride = view.strides[dim] + * if 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memview).to_dtype_func + * else: + */ + __pyx_t_3 = ((struct __pyx_memoryviewslice_obj *)__pyx_v_memview)->to_object_func; + __pyx_v_to_object_func = __pyx_t_3; + + /* "View.MemoryView":1049 + * if isinstance(memview, _memoryviewslice): + * to_object_func = (<_memoryviewslice> memview).to_object_func + * to_dtype_func = (<_memoryviewslice> memview).to_dtype_func # <<<<<<<<<<<<<< + * else: + * to_object_func = NULL + */ + __pyx_t_4 = ((struct __pyx_memoryviewslice_obj *)__pyx_v_memview)->to_dtype_func; + __pyx_v_to_dtype_func = __pyx_t_4; + goto __pyx_L3; + } + /*else*/ { + + /* "View.MemoryView":1051 + * to_dtype_func = (<_memoryviewslice> memview).to_dtype_func + * else: + * to_object_func = NULL # <<<<<<<<<<<<<< + * to_dtype_func = NULL + * + */ + __pyx_v_to_object_func = NULL; + + /* "View.MemoryView":1052 + * else: + * to_object_func = NULL + * to_dtype_func = NULL # <<<<<<<<<<<<<< + * + * return memoryview_fromslice(memviewslice[0], memview.view.ndim, + */ + __pyx_v_to_dtype_func = NULL; + } + __pyx_L3:; + + /* "View.MemoryView":1054 + * to_dtype_func = NULL + * + * return memoryview_fromslice(memviewslice[0], memview.view.ndim, # <<<<<<<<<<<<<< + * to_object_func, to_dtype_func, + * memview.dtype_is_object) + */ + __Pyx_XDECREF(__pyx_r); + + /* "View.MemoryView":1056 + * return memoryview_fromslice(memviewslice[0], memview.view.ndim, + * to_object_func, to_dtype_func, + * memview.dtype_is_object) # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_5 = __pyx_memoryview_fromslice((__pyx_v_memviewslice[0]), __pyx_v_memview->view.ndim, __pyx_v_to_object_func, __pyx_v_to_dtype_func, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1054; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_5); + __pyx_r = __pyx_t_5; + __pyx_t_5 = 0; + goto __pyx_L0; + + /* "View.MemoryView":1040 + * + * @cname('__pyx_memoryview_copy_object_from_slice') + * cdef memoryview_copy_from_slice(memoryview memview, __Pyx_memviewslice *memviewslice): # <<<<<<<<<<<<<< + * """ + * Create a new memoryview object from a given memoryview object and slice. + */ + + /* function exit code */ + __pyx_L1_error:; + __Pyx_XDECREF(__pyx_t_5); + __Pyx_AddTraceback("View.MemoryView.memoryview_copy_from_slice", __pyx_clineno, __pyx_lineno, __pyx_filename); + __pyx_r = 0; + __pyx_L0:; + __Pyx_XGIVEREF(__pyx_r); + __Pyx_RefNannyFinishContext(); + return __pyx_r; +} + +/* "View.MemoryView":1062 + * + * + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<< + * if arg < 0: + * return -arg + */ + +static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { + Py_ssize_t __pyx_r; + int __pyx_t_1; + + /* "View.MemoryView":1063 + * + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: + * if arg < 0: # <<<<<<<<<<<<<< + * return -arg + * else: + */ + __pyx_t_1 = ((__pyx_v_arg < 0) != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1064 + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: + * if arg < 0: + * return -arg # <<<<<<<<<<<<<< + * else: + * return arg + */ + __pyx_r = (-__pyx_v_arg); + goto __pyx_L0; + } + /*else*/ { + + /* "View.MemoryView":1066 + * return -arg + * else: + * return arg # <<<<<<<<<<<<<< + * + * @cname('__pyx_get_best_slice_order') + */ + __pyx_r = __pyx_v_arg; + goto __pyx_L0; + } + + /* "View.MemoryView":1062 + * + * + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<< + * if arg < 0: + * return -arg + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1069 + * + * @cname('__pyx_get_best_slice_order') + * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< + * """ + * Figure out the best memory access order for a given slice. + */ + +static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim) { + int __pyx_v_i; + Py_ssize_t __pyx_v_c_stride; + Py_ssize_t __pyx_v_f_stride; + char __pyx_r; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + + /* "View.MemoryView":1074 + * """ + * cdef int i + * cdef Py_ssize_t c_stride = 0 # <<<<<<<<<<<<<< + * cdef Py_ssize_t f_stride = 0 + * + */ + __pyx_v_c_stride = 0; + + /* "View.MemoryView":1075 + * cdef int i + * cdef Py_ssize_t c_stride = 0 + * cdef Py_ssize_t f_stride = 0 # <<<<<<<<<<<<<< + * + * for i in range(ndim - 1, -1, -1): + */ + __pyx_v_f_stride = 0; + + /* "View.MemoryView":1077 + * cdef Py_ssize_t f_stride = 0 + * + * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< + * if mslice.shape[i] > 1: + * c_stride = mslice.strides[i] + */ + for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) { + __pyx_v_i = __pyx_t_1; + + /* "View.MemoryView":1078 + * + * for i in range(ndim - 1, -1, -1): + * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< + * c_stride = mslice.strides[i] + * break + */ + __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1079 + * for i in range(ndim - 1, -1, -1): + * if mslice.shape[i] > 1: + * c_stride = mslice.strides[i] # <<<<<<<<<<<<<< + * break + * + */ + __pyx_v_c_stride = (__pyx_v_mslice->strides[__pyx_v_i]); + + /* "View.MemoryView":1080 + * if mslice.shape[i] > 1: + * c_stride = mslice.strides[i] + * break # <<<<<<<<<<<<<< + * + * for i in range(ndim): + */ + goto __pyx_L4_break; + } + } + __pyx_L4_break:; + + /* "View.MemoryView":1082 + * break + * + * for i in range(ndim): # <<<<<<<<<<<<<< + * if mslice.shape[i] > 1: + * f_stride = mslice.strides[i] + */ + __pyx_t_1 = __pyx_v_ndim; + for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_1; __pyx_t_3+=1) { + __pyx_v_i = __pyx_t_3; + + /* "View.MemoryView":1083 + * + * for i in range(ndim): + * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< + * f_stride = mslice.strides[i] + * break + */ + __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1084 + * for i in range(ndim): + * if mslice.shape[i] > 1: + * f_stride = mslice.strides[i] # <<<<<<<<<<<<<< + * break + * + */ + __pyx_v_f_stride = (__pyx_v_mslice->strides[__pyx_v_i]); + + /* "View.MemoryView":1085 + * if mslice.shape[i] > 1: + * f_stride = mslice.strides[i] + * break # <<<<<<<<<<<<<< + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): + */ + goto __pyx_L7_break; + } + } + __pyx_L7_break:; + + /* "View.MemoryView":1087 + * break + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< + * return 'C' + * else: + */ + __pyx_t_2 = ((abs_py_ssize_t(__pyx_v_c_stride) <= abs_py_ssize_t(__pyx_v_f_stride)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1088 + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): + * return 'C' # <<<<<<<<<<<<<< + * else: + * return 'F' + */ + __pyx_r = 'C'; + goto __pyx_L0; + } + /*else*/ { + + /* "View.MemoryView":1090 + * return 'C' + * else: + * return 'F' # <<<<<<<<<<<<<< + * + * @cython.cdivision(True) + */ + __pyx_r = 'F'; + goto __pyx_L0; + } + + /* "View.MemoryView":1069 + * + * @cname('__pyx_get_best_slice_order') + * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< + * """ + * Figure out the best memory access order for a given slice. + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1093 + * + * @cython.cdivision(True) + * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< + * char *dst_data, Py_ssize_t *dst_strides, + * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, + */ + +static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v_src_strides, char *__pyx_v_dst_data, Py_ssize_t *__pyx_v_dst_strides, Py_ssize_t *__pyx_v_src_shape, Py_ssize_t *__pyx_v_dst_shape, int __pyx_v_ndim, size_t __pyx_v_itemsize) { + CYTHON_UNUSED Py_ssize_t __pyx_v_i; + CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent; + Py_ssize_t __pyx_v_dst_extent; + Py_ssize_t __pyx_v_src_stride; + Py_ssize_t __pyx_v_dst_stride; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + Py_ssize_t __pyx_t_4; + Py_ssize_t __pyx_t_5; + + /* "View.MemoryView":1100 + * + * cdef Py_ssize_t i + * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] + */ + __pyx_v_src_extent = (__pyx_v_src_shape[0]); + + /* "View.MemoryView":1101 + * cdef Py_ssize_t i + * cdef Py_ssize_t src_extent = src_shape[0] + * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t src_stride = src_strides[0] + * cdef Py_ssize_t dst_stride = dst_strides[0] + */ + __pyx_v_dst_extent = (__pyx_v_dst_shape[0]); + + /* "View.MemoryView":1102 + * cdef Py_ssize_t src_extent = src_shape[0] + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + */ + __pyx_v_src_stride = (__pyx_v_src_strides[0]); + + /* "View.MemoryView":1103 + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] + * cdef Py_ssize_t dst_stride = dst_strides[0] # <<<<<<<<<<<<<< + * + * if ndim == 1: + */ + __pyx_v_dst_stride = (__pyx_v_dst_strides[0]); + + /* "View.MemoryView":1105 + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + * if ndim == 1: # <<<<<<<<<<<<<< + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + */ + __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1106 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ + __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0); + if (__pyx_t_2) { + goto __pyx_L6_next_and; + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L5_bool_binop_done; + } + __pyx_L6_next_and:; + __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0); + if (__pyx_t_2) { + goto __pyx_L7_next_and; + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L5_bool_binop_done; + } + __pyx_L7_next_and:; + + /* "View.MemoryView":1107 + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< + * memcpy(dst_data, src_data, itemsize * dst_extent) + * else: + */ + __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize); + if (__pyx_t_2) { + __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride)); + } + __pyx_t_3 = (__pyx_t_2 != 0); + __pyx_t_1 = __pyx_t_3; + __pyx_L5_bool_binop_done:; + if (__pyx_t_1) { + + /* "View.MemoryView":1108 + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<< + * else: + * for i in range(dst_extent): + */ + memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent)); + goto __pyx_L4; + } + /*else*/ { + + /* "View.MemoryView":1110 + * memcpy(dst_data, src_data, itemsize * dst_extent) + * else: + * for i in range(dst_extent): # <<<<<<<<<<<<<< + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride + */ + __pyx_t_4 = __pyx_v_dst_extent; + for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { + __pyx_v_i = __pyx_t_5; + + /* "View.MemoryView":1111 + * else: + * for i in range(dst_extent): + * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<< + * src_data += src_stride + * dst_data += dst_stride + */ + memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize); + + /* "View.MemoryView":1112 + * for i in range(dst_extent): + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride # <<<<<<<<<<<<<< + * dst_data += dst_stride + * else: + */ + __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); + + /* "View.MemoryView":1113 + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride + * dst_data += dst_stride # <<<<<<<<<<<<<< + * else: + * for i in range(dst_extent): + */ + __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); + } + } + __pyx_L4:; + goto __pyx_L3; + } + /*else*/ { + + /* "View.MemoryView":1115 + * dst_data += dst_stride + * else: + * for i in range(dst_extent): # <<<<<<<<<<<<<< + * _copy_strided_to_strided(src_data, src_strides + 1, + * dst_data, dst_strides + 1, + */ + __pyx_t_4 = __pyx_v_dst_extent; + for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { + __pyx_v_i = __pyx_t_5; + + /* "View.MemoryView":1116 + * else: + * for i in range(dst_extent): + * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<< + * dst_data, dst_strides + 1, + * src_shape + 1, dst_shape + 1, + */ + _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize); + + /* "View.MemoryView":1120 + * src_shape + 1, dst_shape + 1, + * ndim - 1, itemsize) + * src_data += src_stride # <<<<<<<<<<<<<< + * dst_data += dst_stride + * + */ + __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); + + /* "View.MemoryView":1121 + * ndim - 1, itemsize) + * src_data += src_stride + * dst_data += dst_stride # <<<<<<<<<<<<<< + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, + */ + __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); + } + } + __pyx_L3:; + + /* "View.MemoryView":1093 + * + * @cython.cdivision(True) + * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< + * char *dst_data, Py_ssize_t *dst_strides, + * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, + */ + + /* function exit code */ +} + +/* "View.MemoryView":1123 + * dst_data += dst_stride + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + */ + +static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) { + + /* "View.MemoryView":1126 + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + * _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<< + * src.shape, dst.shape, ndim, itemsize) + * + */ + _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize); + + /* "View.MemoryView":1123 + * dst_data += dst_stride + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + */ + + /* function exit code */ +} + +/* "View.MemoryView":1130 + * + * @cname('__pyx_memoryview_slice_get_size') + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef int i + */ + +static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) { + int __pyx_v_i; + Py_ssize_t __pyx_v_size; + Py_ssize_t __pyx_r; + Py_ssize_t __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + + /* "View.MemoryView":1133 + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef int i + * cdef Py_ssize_t size = src.memview.view.itemsize # <<<<<<<<<<<<<< + * + * for i in range(ndim): + */ + __pyx_t_1 = __pyx_v_src->memview->view.itemsize; + __pyx_v_size = __pyx_t_1; + + /* "View.MemoryView":1135 + * cdef Py_ssize_t size = src.memview.view.itemsize + * + * for i in range(ndim): # <<<<<<<<<<<<<< + * size *= src.shape[i] + * + */ + __pyx_t_2 = __pyx_v_ndim; + for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { + __pyx_v_i = __pyx_t_3; + + /* "View.MemoryView":1136 + * + * for i in range(ndim): + * size *= src.shape[i] # <<<<<<<<<<<<<< + * + * return size + */ + __pyx_v_size = (__pyx_v_size * (__pyx_v_src->shape[__pyx_v_i])); + } + + /* "View.MemoryView":1138 + * size *= src.shape[i] + * + * return size # <<<<<<<<<<<<<< + * + * @cname('__pyx_fill_contig_strides_array') + */ + __pyx_r = __pyx_v_size; + goto __pyx_L0; + + /* "View.MemoryView":1130 + * + * @cname('__pyx_memoryview_slice_get_size') + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef int i + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1141 + * + * @cname('__pyx_fill_contig_strides_array') + * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< + * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride, + * int ndim, char order) nogil: + */ + +static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, Py_ssize_t __pyx_v_stride, int __pyx_v_ndim, char __pyx_v_order) { + int __pyx_v_idx; + Py_ssize_t __pyx_r; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + + /* "View.MemoryView":1150 + * cdef int idx + * + * if order == 'F': # <<<<<<<<<<<<<< + * for idx in range(ndim): + * strides[idx] = stride + */ + __pyx_t_1 = ((__pyx_v_order == 'F') != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1151 + * + * if order == 'F': + * for idx in range(ndim): # <<<<<<<<<<<<<< + * strides[idx] = stride + * stride = stride * shape[idx] + */ + __pyx_t_2 = __pyx_v_ndim; + for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { + __pyx_v_idx = __pyx_t_3; + + /* "View.MemoryView":1152 + * if order == 'F': + * for idx in range(ndim): + * strides[idx] = stride # <<<<<<<<<<<<<< + * stride = stride * shape[idx] + * else: + */ + (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; + + /* "View.MemoryView":1153 + * for idx in range(ndim): + * strides[idx] = stride + * stride = stride * shape[idx] # <<<<<<<<<<<<<< + * else: + * for idx in range(ndim - 1, -1, -1): + */ + __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); + 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__pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_6 == NULL)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1261; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_v_tmpdata = __pyx_t_6; + + /* "View.MemoryView":1262 + * + * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) + * src = tmp # <<<<<<<<<<<<<< + * + * if not broadcasting: + */ + __pyx_v_src = __pyx_v_tmp; + goto __pyx_L9; + } + __pyx_L9:; + + /* "View.MemoryView":1264 + * src = tmp + * + * if not broadcasting: # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_2 = ((!(__pyx_v_broadcasting != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1267 + * + * + * if slice_is_contig(&src, 'C', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(&dst, 'C', ndim) + * elif slice_is_contig(&src, 'F', ndim): + */ + __pyx_t_2 = (__pyx_memviewslice_is_contig((&__pyx_v_src), 'C', __pyx_v_ndim) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1268 + * + * if slice_is_contig(&src, 'C', ndim): + * direct_copy = slice_is_contig(&dst, 'C', ndim) # <<<<<<<<<<<<<< + * elif slice_is_contig(&src, 'F', ndim): + * direct_copy = slice_is_contig(&dst, 'F', ndim) + */ + __pyx_v_direct_copy = __pyx_memviewslice_is_contig((&__pyx_v_dst), 'C', __pyx_v_ndim); + goto __pyx_L12; + } + + /* "View.MemoryView":1269 + * if slice_is_contig(&src, 'C', ndim): + * direct_copy = slice_is_contig(&dst, 'C', ndim) + * elif slice_is_contig(&src, 'F', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(&dst, 'F', ndim) + * + */ + __pyx_t_2 = (__pyx_memviewslice_is_contig((&__pyx_v_src), 'F', __pyx_v_ndim) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1270 + * direct_copy = slice_is_contig(&dst, 'C', ndim) + * elif slice_is_contig(&src, 'F', ndim): + * direct_copy = slice_is_contig(&dst, 'F', ndim) # <<<<<<<<<<<<<< + * + * if direct_copy: + */ + __pyx_v_direct_copy = __pyx_memviewslice_is_contig((&__pyx_v_dst), 'F', __pyx_v_ndim); + goto __pyx_L12; + } + __pyx_L12:; + + /* "View.MemoryView":1272 + * direct_copy = slice_is_contig(&dst, 'F', ndim) + * + * if direct_copy: # <<<<<<<<<<<<<< + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + */ + __pyx_t_2 = (__pyx_v_direct_copy != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1274 + * if direct_copy: + * + * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); + + /* "View.MemoryView":1275 + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) # <<<<<<<<<<<<<< + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) + */ + memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim)); + + /* "View.MemoryView":1276 + * refcount_copying(&dst, dtype_is_object, ndim, False) + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< + * free(tmpdata) + * return 0 + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); + + /* "View.MemoryView":1277 + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) # <<<<<<<<<<<<<< + * return 0 + * + */ + free(__pyx_v_tmpdata); + + /* "View.MemoryView":1278 + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) + * return 0 # <<<<<<<<<<<<<< + * + * if order == 'F' == get_best_order(&dst, ndim): + */ + __pyx_r = 0; + goto __pyx_L0; + } + goto __pyx_L11; + } + __pyx_L11:; + + /* "View.MemoryView":1280 + * return 0 + * + * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_2 = (__pyx_v_order == 'F'); + if (__pyx_t_2) { + __pyx_t_2 = ('F' == __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim)); + } + __pyx_t_7 = (__pyx_t_2 != 0); + if (__pyx_t_7) { + + /* "View.MemoryView":1283 + * + * + * transpose_memslice(&src) # <<<<<<<<<<<<<< + * transpose_memslice(&dst) + * + */ + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1283; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "View.MemoryView":1284 + * + * transpose_memslice(&src) + * transpose_memslice(&dst) # <<<<<<<<<<<<<< + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + */ + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_dst)); if (unlikely(__pyx_t_5 == 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1284; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + goto __pyx_L14; + } + __pyx_L14:; + + /* "View.MemoryView":1286 + * transpose_memslice(&dst) + * + * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< + * copy_strided_to_strided(&src, &dst, ndim, itemsize) + * refcount_copying(&dst, dtype_is_object, ndim, True) + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); + + /* "View.MemoryView":1287 + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + * copy_strided_to_strided(&src, &dst, ndim, itemsize) # <<<<<<<<<<<<<< + * refcount_copying(&dst, dtype_is_object, ndim, True) + * + */ + copy_strided_to_strided((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize); + + /* "View.MemoryView":1288 + * refcount_copying(&dst, dtype_is_object, ndim, False) + * copy_strided_to_strided(&src, &dst, ndim, itemsize) + * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< + * + * free(tmpdata) + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); + + /* "View.MemoryView":1290 + * refcount_copying(&dst, dtype_is_object, ndim, True) + * + * free(tmpdata) # <<<<<<<<<<<<<< + * return 0 + * + */ + free(__pyx_v_tmpdata); + + /* "View.MemoryView":1291 + * + * free(tmpdata) + * return 0 # <<<<<<<<<<<<<< + * + * @cname('__pyx_memoryview_broadcast_leading') + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "View.MemoryView":1222 + * + * @cname('__pyx_memoryview_copy_contents') + * cdef int memoryview_copy_contents(__Pyx_memviewslice src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice dst, + * int src_ndim, int dst_ndim, + */ + + /* function exit code */ + __pyx_L1_error:; + { + #ifdef WITH_THREAD + PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); + #endif + __Pyx_AddTraceback("View.MemoryView.memoryview_copy_contents", __pyx_clineno, __pyx_lineno, __pyx_filename); + #ifdef WITH_THREAD + PyGILState_Release(__pyx_gilstate_save); + #endif + } + __pyx_r = -1; + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1294 + * + * @cname('__pyx_memoryview_broadcast_leading') + * cdef void broadcast_leading(__Pyx_memviewslice *slice, # <<<<<<<<<<<<<< + * int ndim, + * int ndim_other) nogil: + */ + +static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_slice, int __pyx_v_ndim, int __pyx_v_ndim_other) { + int __pyx_v_i; + int __pyx_v_offset; + int __pyx_t_1; + int __pyx_t_2; + + /* "View.MemoryView":1298 + * int ndim_other) nogil: + * cdef int i + * cdef int offset = ndim_other - ndim # <<<<<<<<<<<<<< + * + * for i in range(ndim - 1, -1, -1): + */ + __pyx_v_offset = (__pyx_v_ndim_other - __pyx_v_ndim); + + /* "View.MemoryView":1300 + * cdef int offset = ndim_other - ndim + * + * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< + * slice.shape[i + offset] = slice.shape[i] + * slice.strides[i + offset] = slice.strides[i] + */ + for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) { + __pyx_v_i = __pyx_t_1; + + /* "View.MemoryView":1301 + * + * for i in range(ndim - 1, -1, -1): + * slice.shape[i + offset] = slice.shape[i] # <<<<<<<<<<<<<< + * slice.strides[i + offset] = slice.strides[i] + * slice.suboffsets[i + offset] = slice.suboffsets[i] + */ + (__pyx_v_slice->shape[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_slice->shape[__pyx_v_i]); + + /* "View.MemoryView":1302 + * for i in range(ndim - 1, -1, -1): + * slice.shape[i + offset] = slice.shape[i] + * slice.strides[i + offset] = slice.strides[i] # <<<<<<<<<<<<<< + * slice.suboffsets[i + offset] = slice.suboffsets[i] + * + */ + (__pyx_v_slice->strides[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_slice->strides[__pyx_v_i]); + + /* "View.MemoryView":1303 + * slice.shape[i + offset] = slice.shape[i] + * slice.strides[i + offset] = slice.strides[i] + * slice.suboffsets[i + offset] = slice.suboffsets[i] # <<<<<<<<<<<<<< + * + * for i in range(offset): + */ + (__pyx_v_slice->suboffsets[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_slice->suboffsets[__pyx_v_i]); + } + + /* "View.MemoryView":1305 + * slice.suboffsets[i + offset] = slice.suboffsets[i] + * + * for i in range(offset): # <<<<<<<<<<<<<< + * slice.shape[i] = 1 + * slice.strides[i] = slice.strides[0] + */ + __pyx_t_1 = __pyx_v_offset; + for (__pyx_t_2 = 0; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) { + __pyx_v_i = __pyx_t_2; + + /* "View.MemoryView":1306 + * + * for i in range(offset): + * slice.shape[i] = 1 # <<<<<<<<<<<<<< + * slice.strides[i] = slice.strides[0] + * slice.suboffsets[i] = -1 + */ + (__pyx_v_slice->shape[__pyx_v_i]) = 1; + + /* "View.MemoryView":1307 + * for i in range(offset): + * slice.shape[i] = 1 + * slice.strides[i] = slice.strides[0] # <<<<<<<<<<<<<< + * slice.suboffsets[i] = -1 + * + */ + (__pyx_v_slice->strides[__pyx_v_i]) = (__pyx_v_slice->strides[0]); + + /* "View.MemoryView":1308 + * slice.shape[i] = 1 + * slice.strides[i] = slice.strides[0] + * slice.suboffsets[i] = -1 # <<<<<<<<<<<<<< + * + * + */ + (__pyx_v_slice->suboffsets[__pyx_v_i]) = -1; + } + + /* "View.MemoryView":1294 + * + * @cname('__pyx_memoryview_broadcast_leading') + * cdef void broadcast_leading(__Pyx_memviewslice *slice, # <<<<<<<<<<<<<< + * int ndim, + * int ndim_other) nogil: + */ + + /* function 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*__pyx_v_strides, int __pyx_v_ndim, int __pyx_v_inc) { + CYTHON_UNUSED Py_ssize_t __pyx_v_i; + __Pyx_RefNannyDeclarations + Py_ssize_t __pyx_t_1; + Py_ssize_t __pyx_t_2; + int __pyx_t_3; + __Pyx_RefNannySetupContext("refcount_objects_in_slice", 0); + + /* "View.MemoryView":1335 + * cdef Py_ssize_t i + * + * for i in range(shape[0]): # <<<<<<<<<<<<<< + * if ndim == 1: + * if inc: + */ + __pyx_t_1 = (__pyx_v_shape[0]); + for (__pyx_t_2 = 0; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) { + __pyx_v_i = __pyx_t_2; + + /* "View.MemoryView":1336 + * + * for i in range(shape[0]): + * if ndim == 1: # <<<<<<<<<<<<<< + * if inc: + * Py_INCREF(( data)[0]) + */ + __pyx_t_3 = ((__pyx_v_ndim == 1) != 0); + if (__pyx_t_3) { + + /* "View.MemoryView":1337 + * for i in range(shape[0]): + * if ndim == 1: + * if inc: # <<<<<<<<<<<<<< + * Py_INCREF(( data)[0]) + * else: + */ + __pyx_t_3 = (__pyx_v_inc != 0); + if (__pyx_t_3) { + + /* "View.MemoryView":1338 + * if ndim == 1: + * if inc: + * Py_INCREF(( data)[0]) # <<<<<<<<<<<<<< + * else: + * Py_DECREF(( data)[0]) + */ + Py_INCREF((((PyObject **)__pyx_v_data)[0])); + goto __pyx_L6; + } + /*else*/ { + + /* "View.MemoryView":1340 + * Py_INCREF(( data)[0]) + * else: + * Py_DECREF(( data)[0]) # <<<<<<<<<<<<<< + * else: + * refcount_objects_in_slice(data, shape + 1, strides + 1, + */ + Py_DECREF((((PyObject **)__pyx_v_data)[0])); + } + __pyx_L6:; + goto __pyx_L5; + } + /*else*/ { + + /* "View.MemoryView":1342 + * Py_DECREF(( data)[0]) + * else: + * refcount_objects_in_slice(data, shape + 1, strides + 1, # <<<<<<<<<<<<<< + * ndim - 1, inc) + * + */ + __pyx_memoryview_refcount_objects_in_slice(__pyx_v_data, (__pyx_v_shape + 1), (__pyx_v_strides + 1), (__pyx_v_ndim - 1), __pyx_v_inc); + } + __pyx_L5:; + + /* "View.MemoryView":1345 + * ndim - 1, inc) + * + * data += strides[0] # <<<<<<<<<<<<<< + * + * + */ + __pyx_v_data = (__pyx_v_data + (__pyx_v_strides[0])); + } + + /* "View.MemoryView":1331 + * + * @cname('__pyx_memoryview_refcount_objects_in_slice') 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/* "View.MemoryView":1355 + * bint dtype_is_object) nogil: + * refcount_copying(dst, dtype_is_object, ndim, False) + * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim, # <<<<<<<<<<<<<< + * itemsize, item) + * refcount_copying(dst, dtype_is_object, ndim, True) + */ + __pyx_memoryview__slice_assign_scalar(__pyx_v_dst->data, __pyx_v_dst->shape, __pyx_v_dst->strides, __pyx_v_ndim, __pyx_v_itemsize, __pyx_v_item); + + /* "View.MemoryView":1357 + * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim, + * itemsize, item) + * refcount_copying(dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< + * + * + */ + __pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 1); + + /* "View.MemoryView":1351 + * + * @cname('__pyx_memoryview_slice_assign_scalar') + * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim, # <<<<<<<<<<<<<< + * size_t itemsize, void *item, + * bint dtype_is_object) nogil: + */ + + /* function exit code */ +} + +/* "View.MemoryView":1361 + * + * @cname('__pyx_memoryview__slice_assign_scalar') + * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< + * Py_ssize_t *strides, int ndim, + * size_t itemsize, void *item) nogil: + */ + +static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item) { + CYTHON_UNUSED Py_ssize_t __pyx_v_i; + Py_ssize_t __pyx_v_stride; + Py_ssize_t __pyx_v_extent; + int __pyx_t_1; + Py_ssize_t __pyx_t_2; + Py_ssize_t __pyx_t_3; + + /* "View.MemoryView":1365 + * size_t itemsize, void *item) nogil: + * cdef Py_ssize_t i + * cdef Py_ssize_t stride = strides[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t extent = shape[0] + * + */ + __pyx_v_stride = (__pyx_v_strides[0]); + + /* "View.MemoryView":1366 + * cdef Py_ssize_t i + * cdef Py_ssize_t stride = strides[0] + * cdef Py_ssize_t extent = shape[0] # <<<<<<<<<<<<<< + * + * if ndim == 1: + */ + __pyx_v_extent = (__pyx_v_shape[0]); + + /* "View.MemoryView":1368 + * cdef Py_ssize_t extent = shape[0] + * + * if ndim == 1: # <<<<<<<<<<<<<< + * for i in range(extent): + * memcpy(data, item, itemsize) + */ + __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1369 + * + * if ndim == 1: + * for i in range(extent): # <<<<<<<<<<<<<< + * memcpy(data, item, itemsize) + * data += stride + */ + __pyx_t_2 = __pyx_v_extent; + for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { + __pyx_v_i = __pyx_t_3; + + /* "View.MemoryView":1370 + * if ndim == 1: + * for i in range(extent): + * memcpy(data, item, itemsize) # <<<<<<<<<<<<<< + * data += stride + * else: + */ + memcpy(__pyx_v_data, __pyx_v_item, __pyx_v_itemsize); + + /* "View.MemoryView":1371 + * for i in range(extent): + * memcpy(data, item, itemsize) + * data += stride # <<<<<<<<<<<<<< + * else: + * for i in range(extent): + */ + __pyx_v_data = (__pyx_v_data + __pyx_v_stride); + } + goto __pyx_L3; + } + /*else*/ { + + /* "View.MemoryView":1373 + * data += stride + * else: + * for i in range(extent): # <<<<<<<<<<<<<< + * _slice_assign_scalar(data, shape + 1, strides + 1, + * ndim - 1, itemsize, item) + */ + __pyx_t_2 = __pyx_v_extent; + for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { + __pyx_v_i = __pyx_t_3; + + /* "View.MemoryView":1374 + * else: + * for i in range(extent): + * _slice_assign_scalar(data, shape + 1, strides + 1, # <<<<<<<<<<<<<< + * ndim - 1, itemsize, item) + * data += stride + */ + __pyx_memoryview__slice_assign_scalar(__pyx_v_data, (__pyx_v_shape + 1), (__pyx_v_strides + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize, __pyx_v_item); + + /* "View.MemoryView":1376 + * _slice_assign_scalar(data, shape + 1, strides + 1, + * ndim - 1, itemsize, item) + * data += stride # <<<<<<<<<<<<<< + * + * + */ + __pyx_v_data = (__pyx_v_data + __pyx_v_stride); + } + } + __pyx_L3:; + + /* "View.MemoryView":1361 + * + * 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(unlikely(Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + ++Py_REFCNT(o); + __pyx_array___dealloc__(o); + --Py_REFCNT(o); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->mode); + Py_CLEAR(p->_format); + (*Py_TYPE(o)->tp_free)(o); +} +static PyObject *__pyx_sq_item_array(PyObject *o, Py_ssize_t i) { + PyObject *r; + PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0; + r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); + Py_DECREF(x); + return r; +} + +static int __pyx_mp_ass_subscript_array(PyObject *o, PyObject *i, PyObject *v) { + if (v) { + return __pyx_array___setitem__(o, i, v); + } + else { + PyErr_Format(PyExc_NotImplementedError, + "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name); + return -1; + } +} + +static PyObject *__pyx_tp_getattro_array(PyObject *o, PyObject *n) { + PyObject *v 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PyObject *k) { + struct __pyx_MemviewEnum_obj *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_MemviewEnum_obj *)o); + p->name = Py_None; Py_INCREF(Py_None); + return o; +} + +static void __pyx_tp_dealloc_Enum(PyObject *o) { + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + #if PY_VERSION_HEX >= 0x030400a1 + if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + Py_CLEAR(p->name); + (*Py_TYPE(o)->tp_free)(o); +} + +static int __pyx_tp_traverse_Enum(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + if (p->name) { + e = (*v)(p->name, a); if (e) return e; + } + return 0; +} + +static int 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*__pyx_getprop___pyx_memoryview_shape(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryview_get_shape(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_strides(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryview_get_strides(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_suboffsets(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryview_get_suboffsets(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_ndim(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryview_get_ndim(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_itemsize(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryview_get_itemsize(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_nbytes(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryview_get_nbytes(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_size(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryview_get_size(o); +} + +static PyMethodDef __pyx_methods_memoryview[] = { + {"is_c_contig", (PyCFunction)__pyx_memoryview_is_c_contig, METH_NOARGS, 0}, + {"is_f_contig", (PyCFunction)__pyx_memoryview_is_f_contig, METH_NOARGS, 0}, + {"copy", (PyCFunction)__pyx_memoryview_copy, METH_NOARGS, 0}, + {"copy_fortran", (PyCFunction)__pyx_memoryview_copy_fortran, METH_NOARGS, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets_memoryview[] = { + {(char *)"T", __pyx_getprop___pyx_memoryview_T, 0, 0, 0}, + {(char *)"base", __pyx_getprop___pyx_memoryview_base, 0, 0, 0}, + {(char *)"shape", __pyx_getprop___pyx_memoryview_shape, 0, 0, 0}, + {(char *)"strides", __pyx_getprop___pyx_memoryview_strides, 0, 0, 0}, + {(char *)"suboffsets", __pyx_getprop___pyx_memoryview_suboffsets, 0, 0, 0}, + {(char *)"ndim", __pyx_getprop___pyx_memoryview_ndim, 0, 0, 0}, + {(char *)"itemsize", __pyx_getprop___pyx_memoryview_itemsize, 0, 0, 0}, + {(char *)"nbytes", __pyx_getprop___pyx_memoryview_nbytes, 0, 0, 0}, + {(char *)"size", __pyx_getprop___pyx_memoryview_size, 0, 0, 0}, + {0, 0, 0, 0, 0} +}; + +static PySequenceMethods __pyx_tp_as_sequence_memoryview = { + __pyx_memoryview___len__, /*sq_length*/ + 0, /*sq_concat*/ + 0, /*sq_repeat*/ + __pyx_sq_item_memoryview, /*sq_item*/ + 0, /*sq_slice*/ + 0, /*sq_ass_item*/ + 0, /*sq_ass_slice*/ + 0, /*sq_contains*/ + 0, /*sq_inplace_concat*/ + 0, /*sq_inplace_repeat*/ +}; + +static PyMappingMethods __pyx_tp_as_mapping_memoryview = { + __pyx_memoryview___len__, /*mp_length*/ + __pyx_memoryview___getitem__, /*mp_subscript*/ + __pyx_mp_ass_subscript_memoryview, /*mp_ass_subscript*/ +}; + +static PyBufferProcs __pyx_tp_as_buffer_memoryview = { + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getreadbuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getwritebuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getsegcount*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getcharbuffer*/ + #endif + __pyx_memoryview_getbuffer, /*bf_getbuffer*/ + 0, /*bf_releasebuffer*/ +}; + +static PyTypeObject __pyx_type___pyx_memoryview = { + PyVarObject_HEAD_INIT(0, 0) + "GPy.kern._src.stationary_cython.memoryview", /*tp_name*/ + sizeof(struct __pyx_memoryview_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_memoryview, /*tp_dealloc*/ + 0, /*tp_print*/ + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #else + 0, /*reserved*/ + #endif + __pyx_memoryview___repr__, /*tp_repr*/ + 0, /*tp_as_number*/ + &__pyx_tp_as_sequence_memoryview, /*tp_as_sequence*/ + &__pyx_tp_as_mapping_memoryview, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + __pyx_memoryview___str__, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + &__pyx_tp_as_buffer_memoryview, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + 0, /*tp_doc*/ + __pyx_tp_traverse_memoryview, /*tp_traverse*/ + __pyx_tp_clear_memoryview, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_memoryview, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets_memoryview, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_memoryview, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif +}; +static struct __pyx_vtabstruct__memoryviewslice __pyx_vtable__memoryviewslice; + +static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_memoryviewslice_obj *p; + PyObject *o = __pyx_tp_new_memoryview(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_memoryviewslice_obj *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_memoryview*)__pyx_vtabptr__memoryviewslice; + p->from_object = Py_None; Py_INCREF(Py_None); + p->from_slice.memview = NULL; + return o; +} + +static void __pyx_tp_dealloc__memoryviewslice(PyObject *o) { + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + #if PY_VERSION_HEX >= 0x030400a1 + if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + ++Py_REFCNT(o); + __pyx_memoryviewslice___dealloc__(o); + --Py_REFCNT(o); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->from_object); + PyObject_GC_Track(o); + __pyx_tp_dealloc_memoryview(o); +} + +static int __pyx_tp_traverse__memoryviewslice(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + e = __pyx_tp_traverse_memoryview(o, v, a); if (e) return e; + if (p->from_object) { + e = (*v)(p->from_object, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear__memoryviewslice(PyObject *o) { + PyObject* tmp; + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + __pyx_tp_clear_memoryview(o); + tmp = ((PyObject*)p->from_object); + p->from_object = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + __PYX_XDEC_MEMVIEW(&p->from_slice, 1); + return 0; +} + +static PyObject *__pyx_getprop___pyx_memoryviewslice_base(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryviewslice__get__base(o); +} + +static PyMethodDef __pyx_methods__memoryviewslice[] = { + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets__memoryviewslice[] = { + {(char *)"base", __pyx_getprop___pyx_memoryviewslice_base, 0, 0, 0}, + {0, 0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type___pyx_memoryviewslice = { + PyVarObject_HEAD_INIT(0, 0) + "GPy.kern._src.stationary_cython._memoryviewslice", /*tp_name*/ + sizeof(struct __pyx_memoryviewslice_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc__memoryviewslice, /*tp_dealloc*/ + 0, /*tp_print*/ + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #else + 0, /*reserved*/ + #endif + #if CYTHON_COMPILING_IN_PYPY + __pyx_memoryview___repr__, /*tp_repr*/ + #else + 0, /*tp_repr*/ + #endif + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + #if CYTHON_COMPILING_IN_PYPY + __pyx_memoryview___str__, /*tp_str*/ + #else + 0, /*tp_str*/ + #endif + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + "Internal class for passing memoryview slices to Python", /*tp_doc*/ + __pyx_tp_traverse__memoryviewslice, /*tp_traverse*/ + __pyx_tp_clear__memoryviewslice, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods__memoryviewslice, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets__memoryviewslice, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new__memoryviewslice, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif +}; + static PyMethodDef __pyx_methods[] = { {0, 0, 0, 0} }; @@ -3689,42 +16269,118 @@ static struct PyModuleDef __pyx_moduledef = { #endif static __Pyx_StringTabEntry __pyx_string_tab[] = { + {&__pyx_kp_s_Buffer_view_does_not_expose_stri, __pyx_k_Buffer_view_does_not_expose_stri, sizeof(__pyx_k_Buffer_view_does_not_expose_stri), 0, 0, 1, 0}, + {&__pyx_kp_s_Can_only_create_a_buffer_that_is, 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= 33; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_builtin_ValueError = __Pyx_GetBuiltinName(__pyx_n_s_ValueError); if (!__pyx_builtin_ValueError) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_builtin_range = __Pyx_GetBuiltinName(__pyx_n_s_range); if (!__pyx_builtin_range) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 228; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_builtin_RuntimeError = __Pyx_GetBuiltinName(__pyx_n_s_RuntimeError); if (!__pyx_builtin_RuntimeError) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_MemoryError = __Pyx_GetBuiltinName(__pyx_n_s_MemoryError); if (!__pyx_builtin_MemoryError) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 142; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_enumerate = __Pyx_GetBuiltinName(__pyx_n_s_enumerate); if (!__pyx_builtin_enumerate) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_Ellipsis = __Pyx_GetBuiltinName(__pyx_n_s_Ellipsis); if (!__pyx_builtin_Ellipsis) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 357; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_TypeError = __Pyx_GetBuiltinName(__pyx_n_s_TypeError); if (!__pyx_builtin_TypeError) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 386; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #if PY_MAJOR_VERSION >= 3 + __pyx_builtin_xrange = __Pyx_GetBuiltinName(__pyx_n_s_range); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 514; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #else + __pyx_builtin_xrange = __Pyx_GetBuiltinName(__pyx_n_s_xrange); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 514; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #endif + __pyx_builtin_id = __Pyx_GetBuiltinName(__pyx_n_s_id); if (!__pyx_builtin_id) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 569; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_IndexError = __Pyx_GetBuiltinName(__pyx_n_s_IndexError); if (!__pyx_builtin_IndexError) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 789; __pyx_clineno = __LINE__; goto __pyx_L1_error;} return 0; __pyx_L1_error:; return -1; @@ -3734,7 +16390,7 @@ static int __Pyx_InitCachedConstants(void) { __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__Pyx_InitCachedConstants", 0); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":215 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":215 * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): * raise ValueError(u"ndarray is not C contiguous") # <<<<<<<<<<<<<< @@ -3745,7 +16401,7 @@ static int __Pyx_InitCachedConstants(void) { __Pyx_GOTREF(__pyx_tuple_); __Pyx_GIVEREF(__pyx_tuple_); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":219 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":219 * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): * raise ValueError(u"ndarray is not Fortran contiguous") # <<<<<<<<<<<<<< @@ -3756,7 +16412,7 @@ static int __Pyx_InitCachedConstants(void) { __Pyx_GOTREF(__pyx_tuple__2); __Pyx_GIVEREF(__pyx_tuple__2); - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 + /* "../../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":257 * if ((descr.byteorder == c'>' and little_endian) or * (descr.byteorder == c'<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<< @@ -3767,7 +16423,7 @@ static int __Pyx_InitCachedConstants(void) { __Pyx_GOTREF(__pyx_tuple__3); 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__pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__22); + __Pyx_GIVEREF(__pyx_tuple__22); + __pyx_codeobj__23 = (PyObject*)__Pyx_PyCode_New(7, 0, 11, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__22, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_home_james_work_GPy_GPy_kern__s, __pyx_n_s_lengthscale_grads_in_c, 38, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__23)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "GPy/kern/_src/stationary_cython.pyx":49 + * _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. + * + * def lengthscale_grads(int N, int M, int Q, double[:,:] tmp, double[:,:] X, double[:,:] X2, double[:] grad): # <<<<<<<<<<<<<< + * cdef int q, n, m + * cdef double gradq, dist + */ + __pyx_tuple__24 = PyTuple_Pack(12, __pyx_n_s_N, __pyx_n_s_M, __pyx_n_s_Q, __pyx_n_s_tmp_2, __pyx_n_s_X_2, __pyx_n_s_X2_2, 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__pyx_f[2]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__26); + __Pyx_GIVEREF(__pyx_tuple__26); + + /* "View.MemoryView":277 + * + * cdef generic = Enum("") + * cdef strided = Enum("") # default # <<<<<<<<<<<<<< + * cdef indirect = Enum("") + * + */ + __pyx_tuple__27 = PyTuple_Pack(1, __pyx_kp_s_strided_and_direct); if (unlikely(!__pyx_tuple__27)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 277; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__27); + __Pyx_GIVEREF(__pyx_tuple__27); + + /* "View.MemoryView":278 + * cdef generic = Enum("") + * cdef strided = Enum("") # default + * cdef indirect = Enum("") # <<<<<<<<<<<<<< + * + * + */ + __pyx_tuple__28 = PyTuple_Pack(1, __pyx_kp_s_strided_and_indirect); if (unlikely(!__pyx_tuple__28)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__28); + __Pyx_GIVEREF(__pyx_tuple__28); + + /* 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WITH_THREAD +PyEval_InitThreads(); +#endif + +if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__Pyx_InitStrings(__pyx_string_tab) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}; + __pyx_int_0 = PyInt_FromLong(0); if (unlikely(!__pyx_int_0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_int_1 = PyInt_FromLong(1); if (unlikely(!__pyx_int_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_int_neg_1 = PyInt_FromLong(-1); if (unlikely(!__pyx_int_neg_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} return 0; __pyx_L1_error:; return -1; @@ -3914,9 +16780,41 @@ PyMODINIT_FUNC PyInit_stationary_cython(void) /*--- Constants init code ---*/ if (unlikely(__Pyx_InitCachedConstants() < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} /*--- Global init code ---*/ + generic = Py_None; Py_INCREF(Py_None); + strided = Py_None; Py_INCREF(Py_None); + indirect = Py_None; Py_INCREF(Py_None); + contiguous = Py_None; Py_INCREF(Py_None); + indirect_contiguous = Py_None; Py_INCREF(Py_None); /*--- Variable export code ---*/ /*--- Function export code ---*/ /*--- Type init code ---*/ + if (PyType_Ready(&__pyx_type___pyx_array) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 99; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_type___pyx_array.tp_print = 0; + __pyx_array_type = &__pyx_type___pyx_array; + if (PyType_Ready(&__pyx_type___pyx_MemviewEnum) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 269; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_type___pyx_MemviewEnum.tp_print = 0; + __pyx_MemviewEnum_type = &__pyx_type___pyx_MemviewEnum; + __pyx_vtabptr_memoryview = &__pyx_vtable_memoryview; + __pyx_vtable_memoryview.get_item_pointer = (char *(*)(struct __pyx_memoryview_obj *, PyObject *))__pyx_memoryview_get_item_pointer; + __pyx_vtable_memoryview.is_slice = (PyObject *(*)(struct __pyx_memoryview_obj *, PyObject *))__pyx_memoryview_is_slice; + __pyx_vtable_memoryview.setitem_slice_assignment = (PyObject *(*)(struct __pyx_memoryview_obj *, PyObject *, PyObject *))__pyx_memoryview_setitem_slice_assignment; + __pyx_vtable_memoryview.setitem_slice_assign_scalar = (PyObject *(*)(struct __pyx_memoryview_obj *, struct __pyx_memoryview_obj *, PyObject *))__pyx_memoryview_setitem_slice_assign_scalar; + __pyx_vtable_memoryview.setitem_indexed = (PyObject *(*)(struct __pyx_memoryview_obj *, PyObject *, PyObject *))__pyx_memoryview_setitem_indexed; + __pyx_vtable_memoryview.convert_item_to_object = (PyObject *(*)(struct __pyx_memoryview_obj *, char *))__pyx_memoryview_convert_item_to_object; + __pyx_vtable_memoryview.assign_item_from_object = (PyObject *(*)(struct __pyx_memoryview_obj *, char *, PyObject *))__pyx_memoryview_assign_item_from_object; + if (PyType_Ready(&__pyx_type___pyx_memoryview) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 302; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_type___pyx_memoryview.tp_print = 0; + if (__Pyx_SetVtable(__pyx_type___pyx_memoryview.tp_dict, __pyx_vtabptr_memoryview) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 302; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_memoryview_type = &__pyx_type___pyx_memoryview; + __pyx_vtabptr__memoryviewslice = &__pyx_vtable__memoryviewslice; + __pyx_vtable__memoryviewslice.__pyx_base = *__pyx_vtabptr_memoryview; + __pyx_vtable__memoryviewslice.__pyx_base.convert_item_to_object = (PyObject *(*)(struct __pyx_memoryview_obj *, char *))__pyx_memoryviewslice_convert_item_to_object; + __pyx_vtable__memoryviewslice.__pyx_base.assign_item_from_object = (PyObject *(*)(struct __pyx_memoryview_obj *, char *, PyObject *))__pyx_memoryviewslice_assign_item_from_object; + 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(PyDict_SetItem(__pyx_d, __pyx_n_s_lengthscale_grads, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "GPy/kern/_src/stationary_cython.pyx":1 * #cython: boundscheck=False # <<<<<<<<<<<<<< + * #cython: nonecheck=False * #cython: wraparound=False - * import numpy as np */ __pyx_t_1 = PyDict_New(); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); if (PyDict_SetItem(__pyx_d, __pyx_n_s_test, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":976 - * arr.base = baseptr + /* "View.MemoryView":203 + * info.obj = self * - * cdef inline object get_array_base(ndarray arr): # <<<<<<<<<<<<<< - * if arr.base is NULL: - * return None + * __pyx_getbuffer = capsule( &__pyx_array_getbuffer, "getbuffer(obj, view, flags)") # <<<<<<<<<<<<<< + * + * def __dealloc__(array self): + */ + __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_array_getbuffer)), __pyx_k_getbuffer_obj_view_flags); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 203; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + if (PyDict_SetItem(__pyx_array_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 203; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; + PyType_Modified(__pyx_array_type); + + /* "View.MemoryView":276 + * return self.name + * + * cdef generic = Enum("") # <<<<<<<<<<<<<< + * cdef strided = Enum("") # default + * cdef indirect = Enum("") + */ + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__26, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + __Pyx_XGOTREF(generic); + __Pyx_DECREF_SET(generic, __pyx_t_1); + __Pyx_GIVEREF(__pyx_t_1); + __pyx_t_1 = 0; + + /* "View.MemoryView":277 + * + * cdef generic = Enum("") + * cdef strided = Enum("") # default # <<<<<<<<<<<<<< + * cdef indirect = Enum("") + * + */ + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__27, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 277; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + __Pyx_XGOTREF(strided); + __Pyx_DECREF_SET(strided, __pyx_t_1); + __Pyx_GIVEREF(__pyx_t_1); + __pyx_t_1 = 0; + + /* "View.MemoryView":278 + * cdef generic = Enum("") + * cdef strided = Enum("") # default + * cdef indirect = Enum("") # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__28, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + __Pyx_XGOTREF(indirect); + __Pyx_DECREF_SET(indirect, __pyx_t_1); + __Pyx_GIVEREF(__pyx_t_1); + __pyx_t_1 = 0; + + /* "View.MemoryView":281 + * + * + * cdef contiguous = Enum("") # <<<<<<<<<<<<<< + * cdef indirect_contiguous = Enum("") + * + */ + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__29, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 281; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + __Pyx_XGOTREF(contiguous); + __Pyx_DECREF_SET(contiguous, __pyx_t_1); + __Pyx_GIVEREF(__pyx_t_1); + __pyx_t_1 = 0; + + /* "View.MemoryView":282 + * + * cdef contiguous = Enum("") + * cdef indirect_contiguous = Enum("") # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__30, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + __Pyx_XGOTREF(indirect_contiguous); + __Pyx_DECREF_SET(indirect_contiguous, __pyx_t_1); + __Pyx_GIVEREF(__pyx_t_1); + __pyx_t_1 = 0; + + /* "View.MemoryView":496 + * info.obj = self + * + * __pyx_getbuffer = capsule( &__pyx_memoryview_getbuffer, "getbuffer(obj, view, flags)") # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), __pyx_k_getbuffer_obj_view_flags); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 496; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + if (PyDict_SetItem(__pyx_memoryview_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 496; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; + PyType_Modified(__pyx_memoryview_type); + + /* "View.MemoryView":953 + * return self.from_object + * + * __pyx_getbuffer = capsule( &__pyx_memoryview_getbuffer, "getbuffer(obj, view, flags)") # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), __pyx_k_getbuffer_obj_view_flags); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 953; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + if (PyDict_SetItem(__pyx_memoryviewslice_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 953; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; + PyType_Modified(__pyx_memoryviewslice_type); + + /* "View.MemoryView":1361 + * + * @cname('__pyx_memoryview__slice_assign_scalar') + * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< + * Py_ssize_t *strides, int ndim, + * size_t itemsize, void *item) nogil: */ /*--- Wrapped vars code ---*/ @@ -4028,6 +17059,19 @@ end: } #endif +static PyObject *__Pyx_GetBuiltinName(PyObject *name) { + PyObject* result = __Pyx_PyObject_GetAttrStr(__pyx_b, name); + if (unlikely(!result)) { + PyErr_Format(PyExc_NameError, +#if PY_MAJOR_VERSION >= 3 + "name '%U' is not defined", name); +#else + "name '%.200s' is not defined", PyString_AS_STRING(name)); +#endif + } + return result; +} + static void __Pyx_RaiseArgtupleInvalid( const char* func_name, int exact, @@ -4773,18 +17817,153 @@ static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyOb #endif } -static PyObject *__Pyx_GetBuiltinName(PyObject *name) { - PyObject* result = __Pyx_PyObject_GetAttrStr(__pyx_b, name); - if (unlikely(!result)) { - PyErr_Format(PyExc_NameError, -#if PY_MAJOR_VERSION >= 3 - "name '%U' is not defined", name); -#else - "name '%.200s' is not defined", PyString_AS_STRING(name)); -#endif +static CYTHON_INLINE int __Pyx_div_int(int a, int b) { + int q = a / b; + int r = a - q*b; + q -= ((r != 0) & ((r ^ b) < 0)); + return q; +} + +static CYTHON_INLINE int __Pyx_mod_int(int a, int b) { + int r = a % b; + r += ((r != 0) & ((r ^ b) < 0)) * b; + return r; +} + +static int +__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, + int ndim, + __Pyx_memviewslice *memviewslice, + int memview_is_new_reference) +{ + __Pyx_RefNannyDeclarations + int i, retval=-1; + Py_buffer *buf = &memview->view; + __Pyx_RefNannySetupContext("init_memviewslice", 0); + if (!buf) { + PyErr_SetString(PyExc_ValueError, + "buf is NULL."); + goto fail; + } else if (memviewslice->memview || memviewslice->data) { + PyErr_SetString(PyExc_ValueError, + "memviewslice is already initialized!"); + goto fail; } + if (buf->strides) { + for (i = 0; i < ndim; i++) { + memviewslice->strides[i] = buf->strides[i]; + } + } else { + Py_ssize_t stride = buf->itemsize; + for (i = ndim - 1; i >= 0; i--) { + memviewslice->strides[i] = stride; + stride *= buf->shape[i]; + } + } + for (i = 0; i < ndim; i++) { + memviewslice->shape[i] = buf->shape[i]; + if (buf->suboffsets) { + memviewslice->suboffsets[i] = buf->suboffsets[i]; + } else { + memviewslice->suboffsets[i] = -1; + } + } + memviewslice->memview = memview; + memviewslice->data = (char *)buf->buf; + if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) { + Py_INCREF(memview); + } + retval = 0; + goto no_fail; +fail: + memviewslice->memview = 0; + memviewslice->data = 0; + retval = -1; +no_fail: + __Pyx_RefNannyFinishContext(); + return retval; +} +static CYTHON_INLINE void __pyx_fatalerror(const char *fmt, ...) { + va_list vargs; + char msg[200]; + va_start(vargs, fmt); +#ifdef HAVE_STDARG_PROTOTYPES + va_start(vargs, fmt); +#else + va_start(vargs); +#endif + vsnprintf(msg, 200, fmt, vargs); + Py_FatalError(msg); + va_end(vargs); +} +static CYTHON_INLINE int +__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count, + PyThread_type_lock lock) +{ + int result; + PyThread_acquire_lock(lock, 1); + result = (*acquisition_count)++; + PyThread_release_lock(lock); return result; } +static CYTHON_INLINE int +__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count, + PyThread_type_lock lock) +{ + int result; + PyThread_acquire_lock(lock, 1); + result = (*acquisition_count)--; + PyThread_release_lock(lock); + return result; +} +static CYTHON_INLINE void +__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) +{ + int first_time; + struct __pyx_memoryview_obj *memview = memslice->memview; + if (!memview || (PyObject *) memview == Py_None) + return; + if (__pyx_get_slice_count(memview) < 0) + __pyx_fatalerror("Acquisition count is %d (line %d)", + __pyx_get_slice_count(memview), lineno); + first_time = __pyx_add_acquisition_count(memview) == 0; + if (first_time) { + if (have_gil) { + Py_INCREF((PyObject *) memview); + } else { + PyGILState_STATE _gilstate = PyGILState_Ensure(); + Py_INCREF((PyObject *) memview); + PyGILState_Release(_gilstate); + } + } +} +static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, + int have_gil, int lineno) { + int last_time; + struct __pyx_memoryview_obj *memview = memslice->memview; + if (!memview ) { + return; + } else if ((PyObject *) memview == Py_None) { + memslice->memview = NULL; + return; + } + if (__pyx_get_slice_count(memview) <= 0) + __pyx_fatalerror("Acquisition count is %d (line %d)", + __pyx_get_slice_count(memview), lineno); + last_time = __pyx_sub_acquisition_count(memview) == 1; + memslice->data = NULL; + if (last_time) { + if (have_gil) { + Py_CLEAR(memslice->memview); + } else { + PyGILState_STATE _gilstate = PyGILState_Ensure(); + Py_CLEAR(memslice->memview); + PyGILState_Release(_gilstate); + } + } else { + memslice->memview = NULL; + } +} #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { @@ -4981,6 +18160,460 @@ static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { return 0; } +static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) { +#if CYTHON_COMPILING_IN_PYPY + return PyObject_RichCompareBool(s1, s2, equals); +#else + if (s1 == s2) { + return (equals == Py_EQ); + } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) { + const char *ps1, *ps2; + Py_ssize_t length = PyBytes_GET_SIZE(s1); + if (length != PyBytes_GET_SIZE(s2)) + return (equals == Py_NE); + ps1 = PyBytes_AS_STRING(s1); + ps2 = PyBytes_AS_STRING(s2); + if (ps1[0] != ps2[0]) { + return (equals == Py_NE); + } else if (length == 1) { + return (equals == Py_EQ); + } else { + int result = memcmp(ps1, ps2, (size_t)length); + return (equals == Py_EQ) ? (result == 0) : (result != 0); + } + } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) { + return (equals == Py_NE); + } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) { + return (equals == Py_NE); + } else { + int result; + PyObject* py_result = PyObject_RichCompare(s1, s2, equals); + if (!py_result) + return -1; + result = __Pyx_PyObject_IsTrue(py_result); + Py_DECREF(py_result); + return result; + } +#endif +} + +static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) { +#if CYTHON_COMPILING_IN_PYPY + return PyObject_RichCompareBool(s1, s2, equals); +#else +#if PY_MAJOR_VERSION < 3 + PyObject* owned_ref = NULL; +#endif + int s1_is_unicode, s2_is_unicode; + if (s1 == s2) { + goto return_eq; + } + s1_is_unicode = PyUnicode_CheckExact(s1); + s2_is_unicode = PyUnicode_CheckExact(s2); +#if PY_MAJOR_VERSION < 3 + if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) { + owned_ref = PyUnicode_FromObject(s2); + if (unlikely(!owned_ref)) + return -1; + s2 = owned_ref; + s2_is_unicode = 1; + } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) { + owned_ref = PyUnicode_FromObject(s1); + if (unlikely(!owned_ref)) + return -1; + s1 = owned_ref; + s1_is_unicode = 1; + } else if (((!s2_is_unicode) & (!s1_is_unicode))) { + return __Pyx_PyBytes_Equals(s1, s2, equals); + } +#endif + if (s1_is_unicode & s2_is_unicode) { + Py_ssize_t length; + int kind; + void *data1, *data2; + if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0)) + return -1; + length = __Pyx_PyUnicode_GET_LENGTH(s1); + if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) { + goto return_ne; + } + kind = __Pyx_PyUnicode_KIND(s1); + if (kind != __Pyx_PyUnicode_KIND(s2)) { + goto return_ne; + } + data1 = __Pyx_PyUnicode_DATA(s1); + data2 = __Pyx_PyUnicode_DATA(s2); + if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) { + goto return_ne; + } else if (length == 1) { + goto return_eq; + } else { + int result = memcmp(data1, data2, (size_t)(length * kind)); + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_EQ) ? (result == 0) : (result != 0); + } + } else if ((s1 == Py_None) & s2_is_unicode) { + goto return_ne; + } else if ((s2 == Py_None) & s1_is_unicode) { + goto return_ne; + } else { + int result; + PyObject* py_result = PyObject_RichCompare(s1, s2, equals); + if (!py_result) + return -1; + result = __Pyx_PyObject_IsTrue(py_result); + Py_DECREF(py_result); + return result; + } +return_eq: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_EQ); +return_ne: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_NE); +#endif +} + +static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t a, Py_ssize_t b) { + Py_ssize_t q = a / b; + Py_ssize_t r = a - q*b; + q -= ((r != 0) & ((r ^ b) < 0)); + return q; +} + +static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) { +#if CYTHON_COMPILING_IN_CPYTHON +#if PY_MAJOR_VERSION >= 3 + if (likely(PyUnicode_Check(n))) +#else + if (likely(PyString_Check(n))) +#endif + return __Pyx_PyObject_GetAttrStr(o, n); +#endif + return PyObject_GetAttr(o, n); +} + +static CYTHON_INLINE PyObject* __Pyx_decode_c_string( + const char* cstring, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) { + Py_ssize_t length; + if (unlikely((start < 0) | (stop < 0))) { + length = strlen(cstring); + if (start < 0) { + start += length; + if (start < 0) + start = 0; + } + if (stop < 0) + stop += length; + } + length = stop - start; + if (unlikely(length <= 0)) + return PyUnicode_FromUnicode(NULL, 0); + cstring += start; + if (decode_func) { + return decode_func(cstring, length, errors); + } else { + return PyUnicode_Decode(cstring, length, encoding, errors); + } +} + +static CYTHON_INLINE void __Pyx_ExceptionSave(PyObject **type, PyObject **value, PyObject **tb) { +#if CYTHON_COMPILING_IN_CPYTHON + PyThreadState *tstate = PyThreadState_GET(); + *type = tstate->exc_type; + *value = tstate->exc_value; + *tb = tstate->exc_traceback; + Py_XINCREF(*type); + Py_XINCREF(*value); + Py_XINCREF(*tb); +#else + PyErr_GetExcInfo(type, value, tb); +#endif +} +static void __Pyx_ExceptionReset(PyObject *type, PyObject *value, PyObject *tb) { +#if CYTHON_COMPILING_IN_CPYTHON + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyThreadState *tstate = PyThreadState_GET(); + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = type; + tstate->exc_value = value; + tstate->exc_traceback = tb; + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(type, value, tb); +#endif +} + +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) { + PyObject *local_type, *local_value, *local_tb; +#if CYTHON_COMPILING_IN_CPYTHON + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyThreadState *tstate = PyThreadState_GET(); + local_type = tstate->curexc_type; + local_value = tstate->curexc_value; + local_tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +#else + PyErr_Fetch(&local_type, &local_value, &local_tb); +#endif + PyErr_NormalizeException(&local_type, &local_value, &local_tb); +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(tstate->curexc_type)) +#else + if (unlikely(PyErr_Occurred())) +#endif + goto bad; + #if PY_MAJOR_VERSION >= 3 + if (local_tb) { + if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) + goto bad; + } + #endif + Py_XINCREF(local_tb); + Py_XINCREF(local_type); + Py_XINCREF(local_value); + *type = local_type; + *value = local_value; + *tb = local_tb; +#if CYTHON_COMPILING_IN_CPYTHON + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = local_type; + tstate->exc_value = local_value; + tstate->exc_traceback = local_tb; + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(local_type, local_value, local_tb); +#endif + return 0; +bad: + *type = 0; + *value = 0; + *tb = 0; + Py_XDECREF(local_type); + Py_XDECREF(local_value); + Py_XDECREF(local_tb); + return -1; +} + +static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; +#if CYTHON_COMPILING_IN_CPYTHON + PyThreadState *tstate = PyThreadState_GET(); + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = *type; + tstate->exc_value = *value; + tstate->exc_traceback = *tb; +#else + PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb); + PyErr_SetExcInfo(*type, *value, *tb); +#endif + *type = tmp_type; + *value = tmp_value; + *tb = tmp_tb; +} + +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { + PyObject *r; + if (!j) return NULL; + r = PyObject_GetItem(o, j); + Py_DECREF(j); + return r; +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck) { +#if CYTHON_COMPILING_IN_CPYTHON + if (wraparound & unlikely(i < 0)) i += PyList_GET_SIZE(o); + if ((!boundscheck) || likely((0 <= i) & (i < PyList_GET_SIZE(o)))) { + PyObject *r = PyList_GET_ITEM(o, i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck) { +#if CYTHON_COMPILING_IN_CPYTHON + if (wraparound & unlikely(i < 0)) i += PyTuple_GET_SIZE(o); + if ((!boundscheck) || likely((0 <= i) & (i < PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, + int is_list, int wraparound, int boundscheck) { +#if CYTHON_COMPILING_IN_CPYTHON + if (is_list || PyList_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); + if ((!boundscheck) || (likely((n >= 0) & (n < PyList_GET_SIZE(o))))) { + PyObject *r = PyList_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } + else if (PyTuple_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); + if ((!boundscheck) || likely((n >= 0) & (n < PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } else { + PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; + if (likely(m && m->sq_item)) { + if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { + Py_ssize_t l = m->sq_length(o); + if (likely(l >= 0)) { + i += l; + } else { + if (PyErr_ExceptionMatches(PyExc_OverflowError)) + PyErr_Clear(); + else + return NULL; + } + } + return m->sq_item(o, i); + } + } +#else + if (is_list || PySequence_Check(o)) { + return PySequence_GetItem(o, i); + } +#endif + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +} + +static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) { + PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname); +} + +static CYTHON_INLINE long __Pyx_div_long(long a, long b) { + long q = a / b; + long r = a - q*b; + q -= ((r != 0) & ((r ^ b) < 0)); + return q; +} + +static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno, + CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename, + int full_traceback) { + PyObject *old_exc, *old_val, *old_tb; + PyObject *ctx; + __Pyx_ErrFetch(&old_exc, &old_val, &old_tb); + if (full_traceback) { + Py_XINCREF(old_exc); + Py_XINCREF(old_val); + Py_XINCREF(old_tb); + __Pyx_ErrRestore(old_exc, old_val, old_tb); + PyErr_PrintEx(1); + } + #if PY_MAJOR_VERSION < 3 + ctx = PyString_FromString(name); + #else + ctx = PyUnicode_FromString(name); + #endif + __Pyx_ErrRestore(old_exc, old_val, old_tb); + if (!ctx) { + PyErr_WriteUnraisable(Py_None); + } else { + PyErr_WriteUnraisable(ctx); + Py_DECREF(ctx); + } +} + +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { + PyObject *self, *result; + PyCFunction cfunc; + cfunc = PyCFunction_GET_FUNCTION(func); + self = PyCFunction_GET_SELF(func); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = cfunc(self, arg); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +#if CYTHON_COMPILING_IN_CPYTHON +static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_New(1); + if (unlikely(!args)) return NULL; + Py_INCREF(arg); + PyTuple_SET_ITEM(args, 0, arg); + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { +#ifdef __Pyx_CyFunction_USED + if (likely(PyCFunction_Check(func) || PyObject_TypeCheck(func, __pyx_CyFunctionType))) { +#else + if (likely(PyCFunction_Check(func))) { +#endif + if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { + return __Pyx_PyObject_CallMethO(func, arg); + } + } + return __Pyx__PyObject_CallOneArg(func, arg); +} +#else +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject* args = PyTuple_Pack(1, arg); + return (likely(args)) ? __Pyx_PyObject_Call(func, args, NULL) : NULL; +} +#endif + +static int __Pyx_SetVtable(PyObject *dict, void *vtable) { +#if PY_VERSION_HEX >= 0x02070000 + PyObject *ob = PyCapsule_New(vtable, 0, 0); +#else + PyObject *ob = PyCObject_FromVoidPtr(vtable, 0); +#endif + if (!ob) + goto bad; + if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0) + goto bad; + Py_DECREF(ob); + return 0; +bad: + Py_XDECREF(ob); + return -1; +} + static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { int start = 0, mid = 0, end = count - 1; if (end >= 0 && code_line > entries[end].code_line) { @@ -5144,6 +18777,8 @@ bad: static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) return __pyx_pw_5numpy_7ndarray_1__getbuffer__(obj, view, flags); + if (PyObject_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags); + if (PyObject_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags); PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); return -1; } @@ -5161,7 +18796,7 @@ static void __Pyx_ReleaseBuffer(Py_buffer *view) { #endif - static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { + static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { PyObject *empty_list = 0; PyObject *module = 0; PyObject *global_dict = 0; @@ -5350,6 +18985,297 @@ raise_neg_overflow: return (int) -1; } +static int +__pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b) +{ + int i; + if (!a || !b) + return 0; + if (a == b) + return 1; + if (a->size != b->size || a->typegroup != b->typegroup || + a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) { + if (a->typegroup == 'H' || b->typegroup == 'H') { + return a->size == b->size; + } else { + return 0; + } + } + if (a->ndim) { + for (i = 0; i < a->ndim; i++) + if (a->arraysize[i] != b->arraysize[i]) + return 0; + } + if (a->typegroup == 'S') { + if (a->flags != b->flags) + return 0; + if (a->fields || b->fields) { + if (!(a->fields && b->fields)) + return 0; + for (i = 0; a->fields[i].type && b->fields[i].type; i++) { + __Pyx_StructField *field_a = a->fields + i; + __Pyx_StructField *field_b = b->fields + i; + if (field_a->offset != field_b->offset || + !__pyx_typeinfo_cmp(field_a->type, field_b->type)) + return 0; + } + return !a->fields[i].type && !b->fields[i].type; + } + } + return 1; +} + +static int +__pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec) +{ + if (buf->shape[dim] <= 1) + return 1; + if (buf->strides) { + if (spec & __Pyx_MEMVIEW_CONTIG) { + if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) { + if (buf->strides[dim] != sizeof(void *)) { + PyErr_Format(PyExc_ValueError, + "Buffer is not indirectly contiguous " + "in dimension %d.", dim); + goto fail; + } + } else if (buf->strides[dim] != buf->itemsize) { + PyErr_SetString(PyExc_ValueError, + "Buffer and memoryview are not contiguous " + "in the same dimension."); + goto fail; + } + } + if (spec & __Pyx_MEMVIEW_FOLLOW) { + Py_ssize_t stride = buf->strides[dim]; + if (stride < 0) + stride = -stride; + if (stride < buf->itemsize) { + PyErr_SetString(PyExc_ValueError, + "Buffer and memoryview are not contiguous " + "in the same dimension."); + goto fail; + } + } + } else { + if (spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1) { + PyErr_Format(PyExc_ValueError, + "C-contiguous buffer is not contiguous in " + "dimension %d", dim); + goto fail; + } else if (spec & (__Pyx_MEMVIEW_PTR)) { + PyErr_Format(PyExc_ValueError, + "C-contiguous buffer is not indirect in " + "dimension %d", dim); + goto fail; + } else if (buf->suboffsets) { + PyErr_SetString(PyExc_ValueError, + "Buffer exposes suboffsets but no strides"); + goto fail; + } + } + return 1; +fail: + return 0; +} +static int +__pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec) +{ + if (spec & __Pyx_MEMVIEW_DIRECT) { + if (buf->suboffsets && buf->suboffsets[dim] >= 0) { + PyErr_Format(PyExc_ValueError, + "Buffer not compatible with direct access " + "in dimension %d.", dim); + goto fail; + } + } + if (spec & __Pyx_MEMVIEW_PTR) { + if (!buf->suboffsets || (buf->suboffsets && buf->suboffsets[dim] < 0)) { + PyErr_Format(PyExc_ValueError, + "Buffer is not indirectly accessible " + "in dimension %d.", dim); + goto fail; + } + } + return 1; +fail: + return 0; +} +static int +__pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag) +{ + int i; + if (c_or_f_flag & __Pyx_IS_F_CONTIG) { + Py_ssize_t stride = 1; + for (i = 0; i < ndim; i++) { + if (stride * buf->itemsize != buf->strides[i] && + buf->shape[i] > 1) + { + PyErr_SetString(PyExc_ValueError, + "Buffer not fortran contiguous."); + goto fail; + } + stride = stride * buf->shape[i]; + } + } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) { + Py_ssize_t stride = 1; + for (i = ndim - 1; i >- 1; i--) { + if (stride * buf->itemsize != buf->strides[i] && + buf->shape[i] > 1) { + PyErr_SetString(PyExc_ValueError, + "Buffer not C contiguous."); + goto fail; + } + stride = stride * buf->shape[i]; + } + } + return 1; +fail: + return 0; +} +static int __Pyx_ValidateAndInit_memviewslice( + int *axes_specs, + int c_or_f_flag, + int buf_flags, + int ndim, + __Pyx_TypeInfo *dtype, + __Pyx_BufFmt_StackElem stack[], + __Pyx_memviewslice *memviewslice, + PyObject *original_obj) +{ + struct __pyx_memoryview_obj *memview, *new_memview; + __Pyx_RefNannyDeclarations + Py_buffer *buf; + int i, spec = 0, retval = -1; + __Pyx_BufFmt_Context ctx; + int from_memoryview = __pyx_memoryview_check(original_obj); + __Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0); + if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *) + original_obj)->typeinfo)) { + memview = (struct __pyx_memoryview_obj *) original_obj; + new_memview = NULL; + } else { + memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( + original_obj, buf_flags, 0, dtype); + new_memview = memview; + if (unlikely(!memview)) + goto fail; + } + buf = &memview->view; + if (buf->ndim != ndim) { + PyErr_Format(PyExc_ValueError, + "Buffer has wrong number of dimensions (expected %d, got %d)", + ndim, buf->ndim); + goto fail; + } + if (new_memview) { + __Pyx_BufFmt_Init(&ctx, stack, dtype); + if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; + } + if ((unsigned) buf->itemsize != dtype->size) { + PyErr_Format(PyExc_ValueError, + "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) " + "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)", + buf->itemsize, + (buf->itemsize > 1) ? "s" : "", + dtype->name, + dtype->size, + (dtype->size > 1) ? "s" : ""); + goto fail; + } + for (i = 0; i < ndim; i++) { + spec = axes_specs[i]; + if (!__pyx_check_strides(buf, i, ndim, spec)) + goto fail; + if (!__pyx_check_suboffsets(buf, i, ndim, spec)) + goto fail; + } + if (buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag)) + goto fail; + if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice, + new_memview != NULL) == -1)) { + goto fail; + } + retval = 0; + goto no_fail; +fail: + Py_XDECREF(new_memview); + retval = -1; +no_fail: + __Pyx_RefNannyFinishContext(); + return retval; +} + +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_double(PyObject *obj) { + __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; + __Pyx_BufFmt_StackElem stack[1]; + int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; + int retcode; + if (obj == Py_None) { + result.memview = (struct __pyx_memoryview_obj *) Py_None; + return result; + } + retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, + PyBUF_RECORDS, 2, + &__Pyx_TypeInfo_double, stack, + &result, obj); + if (unlikely(retcode == -1)) + goto __pyx_fail; + return result; +__pyx_fail: + result.memview = NULL; + result.data = NULL; + return result; +} + +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_double(PyObject *obj) { + __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; + __Pyx_BufFmt_StackElem stack[1]; + int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; + int retcode; + if (obj == Py_None) { + result.memview = (struct __pyx_memoryview_obj *) Py_None; + return result; + } + retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, + PyBUF_RECORDS, 1, + &__Pyx_TypeInfo_double, stack, + &result, obj); + if (unlikely(retcode == -1)) + goto __pyx_fail; + return result; +__pyx_fail: + result.memview = NULL; + result.data = NULL; + return result; +} + +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { + const int neg_one = (int) -1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(int) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(int) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); + } else if (sizeof(int) <= sizeof(unsigned long long)) { + return PyLong_FromUnsignedLongLong((unsigned long long) value); + } + } else { + if (sizeof(int) <= sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(int) <= sizeof(long long)) { + return PyLong_FromLongLong((long long) value); + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(int), + little, !is_unsigned); + } +} + #if CYTHON_CCOMPLEX #ifdef __cplusplus static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { @@ -5590,30 +19516,139 @@ raise_neg_overflow: #endif #endif -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { - const int neg_one = (int) -1, const_zero = 0; - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(int) < sizeof(long)) { - return PyInt_FromLong((long) value); - } else if (sizeof(int) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); - } else if (sizeof(int) <= sizeof(unsigned long long)) { - return PyLong_FromUnsignedLongLong((unsigned long long) value); - } +static int +__pyx_memviewslice_is_contig(const __Pyx_memviewslice *mvs, + char order, int ndim) +{ + int i, index, step, start; + Py_ssize_t itemsize = mvs->memview->view.itemsize; + if (order == 'F') { + step = 1; + start = 0; } else { - if (sizeof(int) <= sizeof(long)) { - return PyInt_FromLong((long) value); - } else if (sizeof(int) <= sizeof(long long)) { - return PyLong_FromLongLong((long long) value); + step = -1; + start = ndim - 1; + } + for (i = 0; i < ndim; i++) { + index = start + step * i; + if (mvs->suboffsets[index] >= 0 || mvs->strides[index] != itemsize) + return 0; + itemsize *= mvs->shape[index]; + } + return 1; +} + +static void +__pyx_get_array_memory_extents(__Pyx_memviewslice *slice, + void **out_start, void **out_end, + int ndim, size_t itemsize) +{ + char *start, *end; + int i; + start = end = slice->data; + for (i = 0; i < ndim; i++) { + Py_ssize_t stride = slice->strides[i]; + Py_ssize_t extent = slice->shape[i]; + if (extent == 0) { + *out_start = *out_end = start; + return; + } else { + if (stride > 0) + end += stride * (extent - 1); + else + start += stride * (extent - 1); } } - { - int one = 1; int little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&value; - return _PyLong_FromByteArray(bytes, sizeof(int), - little, !is_unsigned); + *out_start = start; + *out_end = end + itemsize; +} +static int +__pyx_slices_overlap(__Pyx_memviewslice *slice1, + __Pyx_memviewslice *slice2, + int ndim, size_t itemsize) +{ + void *start1, *end1, *start2, *end2; + __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize); + __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize); + return (start1 < end2) && (start2 < end1); +} + +static __Pyx_memviewslice +__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, + const char *mode, int ndim, + size_t sizeof_dtype, int contig_flag, + int dtype_is_object) +{ + __Pyx_RefNannyDeclarations + int i; + __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } }; + struct __pyx_memoryview_obj *from_memview = from_mvs->memview; + Py_buffer *buf = &from_memview->view; + PyObject *shape_tuple = NULL; + PyObject *temp_int = NULL; + struct __pyx_array_obj *array_obj = NULL; + struct __pyx_memoryview_obj *memview_obj = NULL; + __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0); + for (i = 0; i < ndim; i++) { + if (from_mvs->suboffsets[i] >= 0) { + PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with " + "indirect dimensions (axis %d)", i); + goto fail; + } } + shape_tuple = PyTuple_New(ndim); + if (unlikely(!shape_tuple)) { + goto fail; + } + __Pyx_GOTREF(shape_tuple); + for(i = 0; i < ndim; i++) { + temp_int = PyInt_FromSsize_t(from_mvs->shape[i]); + if(unlikely(!temp_int)) { + goto fail; + } else { + PyTuple_SET_ITEM(shape_tuple, i, temp_int); + temp_int = NULL; + } + } + array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL); + if (unlikely(!array_obj)) { + goto fail; + } + __Pyx_GOTREF(array_obj); + memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( + (PyObject *) array_obj, contig_flag, + dtype_is_object, + from_mvs->memview->typeinfo); + if (unlikely(!memview_obj)) + goto fail; + if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0)) + goto fail; + if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim, + dtype_is_object) < 0)) + goto fail; + goto no_fail; +fail: + __Pyx_XDECREF(new_mvs.memview); + new_mvs.memview = NULL; + new_mvs.data = NULL; +no_fail: + __Pyx_XDECREF(shape_tuple); + __Pyx_XDECREF(temp_int); + __Pyx_XDECREF(array_obj); + __Pyx_RefNannyFinishContext(); + return new_mvs; +} + +static CYTHON_INLINE PyObject * +__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig) +{ + PyObject *cobj; +#if PY_VERSION_HEX >= 0x02070000 + cobj = PyCapsule_New(p, sig, NULL); +#else + cobj = PyCObject_FromVoidPtr(p, NULL); +#endif + return cobj; } static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { @@ -5642,6 +19677,101 @@ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { } } +static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) { + const char neg_one = (char) -1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(char) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (char) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 + #if CYTHON_USE_PYLONG_INTERNALS + switch (Py_SIZE(x)) { + case 0: return 0; + case 1: __PYX_VERIFY_RETURN_INT(char, digit, ((PyLongObject*)x)->ob_digit[0]); + } + #endif +#endif + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } + if (sizeof(char) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, PyLong_AsUnsignedLong(x)) + } else if (sizeof(char) <= sizeof(unsigned long long)) { + __PYX_VERIFY_RETURN_INT(char, unsigned long long, PyLong_AsUnsignedLongLong(x)) + } + } else { +#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 + #if CYTHON_USE_PYLONG_INTERNALS + switch (Py_SIZE(x)) { + case 0: return 0; + case 1: __PYX_VERIFY_RETURN_INT(char, digit, +(((PyLongObject*)x)->ob_digit[0])); + case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]); + } + #endif +#endif + if (sizeof(char) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT(char, long, PyLong_AsLong(x)) + } else if (sizeof(char) <= sizeof(long long)) { + __PYX_VERIFY_RETURN_INT(char, long long, PyLong_AsLongLong(x)) + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + char val; + PyObject *v = __Pyx_PyNumber_Int(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (char) -1; + } + } else { + char val; + PyObject *tmp = __Pyx_PyNumber_Int(x); + if (!tmp) return (char) -1; + val = __Pyx_PyInt_As_char(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to char"); + return (char) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to char"); + return (char) -1; +} + static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { const long neg_one = (long) -1, const_zero = 0; const int is_unsigned = neg_one > const_zero; diff --git a/GPy/kern/_src/stationary_cython.pyx b/GPy/kern/_src/stationary_cython.pyx index 275e8aef..c550fc91 100644 --- a/GPy/kern/_src/stationary_cython.pyx +++ b/GPy/kern/_src/stationary_cython.pyx @@ -1,7 +1,9 @@ #cython: boundscheck=False +#cython: nonecheck=False #cython: wraparound=False import numpy as np cimport numpy as np +from cython.parallel import prange ctypedef np.float64_t DTYPE_t @@ -22,7 +24,18 @@ def grad_X(int N, int D, int M, cdef double *grad = _grad.data _grad_X(N, D, M, X, X2, tmp, grad) # return nothing, work in place. -def lengthscale_grads(int N, int M, int Q, +def grad_X_cython(int N, int D, int M, double[:,:] X, double[:,:] X2, double[:,:] tmp, double[:,:] grad): + cdef int n,d,nd,m + for nd in prange(N*D, nogil=True): + n = nd/D + d = nd%D + grad[n,d] = 0.0 + for m in range(M): + grad[n,d] += tmp[n,m]*(X[n,d]-X2[m,d]) + + + +def lengthscale_grads_in_c(int N, int M, int Q, np.ndarray[DTYPE_t, ndim=2] _tmp, np.ndarray[DTYPE_t, ndim=2] _X, np.ndarray[DTYPE_t, ndim=2] _X2, @@ -33,4 +46,14 @@ def lengthscale_grads(int N, int M, int Q, cdef double *grad = _grad.data _lengthscale_grads(N, M, Q, tmp, X, X2, grad) # return nothing, work in place. +def lengthscale_grads(int N, int M, int Q, double[:,:] tmp, double[:,:] X, double[:,:] X2, double[:] grad): + cdef int q, n, m + cdef double gradq, dist + for q in range(Q): + grad[q] = 0.0 + for n in range(N): + for m in range(M): + dist = X[n,q] - X2[m,q] + grad[q] += tmp[n,m]*dist*dist + From 8fc00dfdd4403f3bacd41539914dff04ab18c4ca Mon Sep 17 00:00:00 2001 From: James Hensman Date: Tue, 19 May 2015 17:06:53 +0100 Subject: [PATCH 18/41] minor bugfix in mlp kernel --- GPy/kern/_src/mlp.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/kern/_src/mlp.py b/GPy/kern/_src/mlp.py index 4488ea82..e319b8b4 100644 --- a/GPy/kern/_src/mlp.py +++ b/GPy/kern/_src/mlp.py @@ -78,7 +78,7 @@ class MLP(Kern): *((vec1[:, None]+vec2[None, :])*self.weight_variance + 2*self.bias_variance + 2.))*base_cov_grad).sum() - def update_gradients_diag(self, X): + def update_gradients_diag(self, dL_dKdiag, X): self._K_diag_computations(X) self.variance.gradient = np.sum(self._K_diag_dvar*dL_dKdiag) From bfd7734339f38ae8a2a3bc6d7083aa0cb33f4900 Mon Sep 17 00:00:00 2001 From: Max Zwiessele Date: Thu, 21 May 2015 10:15:50 +0200 Subject: [PATCH 19/41] [param] added multilevel indexing note to doc --- GPy/core/parameterization/param.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/GPy/core/parameterization/param.py b/GPy/core/parameterization/param.py index 1838f2bf..91ce9e24 100644 --- a/GPy/core/parameterization/param.py +++ b/GPy/core/parameterization/param.py @@ -38,6 +38,11 @@ class Param(Parameterizable, ObsAr): Fixing parameters will fix them to the value they are right now. If you change the fixed value, it will be fixed to the new value! + Important Note: + Multilevel indexing (e.g. self[:2][1:]) is not supported and might lead to unexpected behaviour. + Try to index in one go, using boolean indexing or the numpy builtin + np.index function. + See :py:class:`GPy.core.parameterized.Parameterized` for more details on constraining etc. """ From b8508cc20c82c01b72b6c2e2b40ec0e1f7bd27a3 Mon Sep 17 00:00:00 2001 From: Zhenwen Dai Date: Thu, 21 May 2015 11:33:37 +0100 Subject: [PATCH 20/41] [ssgplvm] group spike --- GPy/core/parameterization/variational.py | 41 +++++++++++++++++++----- GPy/models/ss_gplvm.py | 12 +++---- 2 files changed, 39 insertions(+), 14 deletions(-) diff --git a/GPy/core/parameterization/variational.py b/GPy/core/parameterization/variational.py index 09191c0b..377c1d4c 100644 --- a/GPy/core/parameterization/variational.py +++ b/GPy/core/parameterization/variational.py @@ -36,8 +36,9 @@ class NormalPrior(VariationalPrior): variational_posterior.variance.gradient -= (1. - (1. / (variational_posterior.variance))) * 0.5 class SpikeAndSlabPrior(VariationalPrior): - def __init__(self, pi=None, learnPi=False, variance = 1.0, name='SpikeAndSlabPrior', **kw): - super(SpikeAndSlabPrior, self).__init__(name=name, **kw) + def __init__(self, pi=None, learnPi=False, variance = 1.0, group_spike=False, name='SpikeAndSlabPrior', **kw): + super(SpikeAndSlabPrior, self).__init__(name=name, **kw) + self.group_spike = group_spike self.variance = Param('variance',variance) self.learnPi = learnPi if learnPi: @@ -50,7 +51,10 @@ class SpikeAndSlabPrior(VariationalPrior): def KL_divergence(self, variational_posterior): mu = variational_posterior.mean S = variational_posterior.variance - gamma = variational_posterior.gamma.values + if self.group_spike: + gamma = variational_posterior.gamma.values[0] + else: + gamma = variational_posterior.gamma.values if len(self.pi.shape)==2: idx = np.unique(variational_posterior.gamma._raveled_index()/gamma.shape[-1]) pi = self.pi[idx] @@ -65,14 +69,21 @@ class SpikeAndSlabPrior(VariationalPrior): def update_gradients_KL(self, variational_posterior): mu = variational_posterior.mean S = variational_posterior.variance - gamma = variational_posterior.gamma.values + if self.group_spike: + gamma = variational_posterior.gamma.values[0] + else: + gamma = variational_posterior.gamma.values if len(self.pi.shape)==2: idx = np.unique(variational_posterior.gamma._raveled_index()/gamma.shape[-1]) pi = self.pi[idx] else: pi = self.pi - variational_posterior.binary_prob.gradient -= np.log((1-pi)/pi*gamma/(1.-gamma))+((np.square(mu)+S)/self.variance-np.log(S)+np.log(self.variance)-1.)/2. + if self.group_spike: + dgamma = np.log((1-pi)/pi*gamma/(1.-gamma))/mu.shape[0] + else: + dgamma = np.log((1-pi)/pi*gamma/(1.-gamma)) + variational_posterior.binary_prob.gradient -= dgamma+((np.square(mu)+S)/self.variance-np.log(S)+np.log(self.variance)-1.)/2. mu.gradient -= gamma*mu/self.variance S.gradient -= (1./self.variance - 1./S) * gamma /2. if self.learnPi: @@ -154,13 +165,27 @@ class SpikeAndSlabPosterior(VariationalPosterior): ''' The SpikeAndSlab distribution for variational approximations. ''' - def __init__(self, means, variances, binary_prob, name='latent space'): + def __init__(self, means, variances, binary_prob, group_spike=False, name='latent space'): """ binary_prob : the probability of the distribution on the slab part. """ super(SpikeAndSlabPosterior, self).__init__(means, variances, name) - self.gamma = Param("binary_prob",binary_prob,Logistic(0.,1.)) - self.link_parameter(self.gamma) + self.group_spike = group_spike + if group_spike: + self.gamma_group = Param("binary_prob_group",binary_prob.mean(axis=0),Logistic(0.,1.)) + self.gamma = Param("binary_prob",binary_prob, __fixed__) + self.link_parameters(self.gamma_group,self.gamma) + else: + self.gamma = Param("binary_prob",binary_prob,Logistic(0.,1.)) + self.link_parameter(self.gamma) + + def propogate_val(self): + if self.group_spike: + self.gamma.param_array.values.reshape(self.gamma.shape)[:] = self.gamma_group.values + + def collate_gradient(self): + if self.group_spike: + self.gamma_group.gradient = self.gamma.gradient.reshape(self.gamma.shape).sum(axis=0) def set_gradients(self, grad): self.mean.gradient, self.variance.gradient, self.gamma.gradient = grad diff --git a/GPy/models/ss_gplvm.py b/GPy/models/ss_gplvm.py index 44eea74c..c2b7c0d0 100644 --- a/GPy/models/ss_gplvm.py +++ b/GPy/models/ss_gplvm.py @@ -103,7 +103,7 @@ class SSGPLVM(SparseGP_MPI): """ def __init__(self, Y, input_dim, X=None, X_variance=None, Gamma=None, init='PCA', num_inducing=10, - Z=None, kernel=None, inference_method=None, likelihood=None, name='Spike_and_Slab GPLVM', group_spike=False, mpi_comm=None, pi=None, learnPi=True,normalizer=False, **kwargs): + Z=None, kernel=None, inference_method=None, likelihood=None, name='Spike_and_Slab GPLVM', group_spike=False, mpi_comm=None, pi=None, learnPi=False,normalizer=False, **kwargs): self.group_spike = group_spike @@ -144,15 +144,12 @@ class SSGPLVM(SparseGP_MPI): if pi is None: pi = np.empty((input_dim)) pi[:] = 0.5 - self.variational_prior = SpikeAndSlabPrior(pi=pi,learnPi=learnPi) # the prior probability of the latent binary variable b + self.variational_prior = SpikeAndSlabPrior(pi=pi,learnPi=learnPi, group_spike=group_spike) # the prior probability of the latent binary variable b - X = SpikeAndSlabPosterior(X, X_variance, gamma) + X = SpikeAndSlabPosterior(X, X_variance, gamma, group_spike=group_spike) super(SSGPLVM,self).__init__(X, Y, Z, kernel, likelihood, variational_prior=self.variational_prior, inference_method=inference_method, name=name, mpi_comm=mpi_comm, normalizer=normalizer, **kwargs) self.link_parameter(self.X, index=0) - - if self.group_spike: - [self.X.gamma[:,i].tie('tieGamma'+str(i)) for i in range(self.X.gamma.shape[1])] # Tie columns together def set_X_gradients(self, X, X_grad): """Set the gradients of the posterior distribution of X in its specific form.""" @@ -163,8 +160,10 @@ class SSGPLVM(SparseGP_MPI): return X.mean.gradient, X.variance.gradient, X.binary_prob.gradient def parameters_changed(self): + self.X.propogate_val() super(SSGPLVM,self).parameters_changed() if isinstance(self.inference_method, VarDTC_minibatch): + self.X.collate_gradient() return self._log_marginal_likelihood -= self.variational_prior.KL_divergence(self.X) @@ -173,6 +172,7 @@ class SSGPLVM(SparseGP_MPI): # update for the KL divergence self.variational_prior.update_gradients_KL(self.X) + self.X.collate_gradient() def input_sensitivity(self): if self.kern.ARD: From afa06214882acccd51c3dfc41976379f132499e0 Mon Sep 17 00:00:00 2001 From: Zhenwen Dai Date: Thu, 21 May 2015 14:18:32 +0100 Subject: [PATCH 21/41] [ssgplvm] implement IBP prior --- GPy/core/gp.py | 3 +- GPy/core/parameterization/variational.py | 4 +- GPy/examples/dimensionality_reduction.py | 4 +- GPy/models/ss_gplvm.py | 54 +++++++++++++----------- 4 files changed, 34 insertions(+), 31 deletions(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 63316384..89313ae2 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -208,8 +208,7 @@ class GP(Model): Kxx = kern.Kdiag(_Xnew) var = Kxx - np.sum(WiKx*Kx, 0) var = var.reshape(-1, 1) - - var[var<0.] = 0. + var[var<0.] = 0. #force mu to be a column vector if len(mu.shape)==1: mu = mu[:,None] diff --git a/GPy/core/parameterization/variational.py b/GPy/core/parameterization/variational.py index 377c1d4c..16192845 100644 --- a/GPy/core/parameterization/variational.py +++ b/GPy/core/parameterization/variational.py @@ -172,11 +172,11 @@ class SpikeAndSlabPosterior(VariationalPosterior): super(SpikeAndSlabPosterior, self).__init__(means, variances, name) self.group_spike = group_spike if group_spike: - self.gamma_group = Param("binary_prob_group",binary_prob.mean(axis=0),Logistic(0.,1.)) + self.gamma_group = Param("binary_prob_group",binary_prob.mean(axis=0),Logistic(1e-6,1.-1e-6)) self.gamma = Param("binary_prob",binary_prob, __fixed__) self.link_parameters(self.gamma_group,self.gamma) else: - self.gamma = Param("binary_prob",binary_prob,Logistic(0.,1.)) + self.gamma = Param("binary_prob",binary_prob,Logistic(1e-6,1.-1e-6)) self.link_parameter(self.gamma) def propogate_val(self): diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py index 37870581..cccb2496 100644 --- a/GPy/examples/dimensionality_reduction.py +++ b/GPy/examples/dimensionality_reduction.py @@ -353,9 +353,9 @@ def ssgplvm_simulation(optimize=True, verbose=1, Y = Ylist[0] k = kern.Linear(Q, ARD=True) # + kern.white(Q, _np.exp(-2)) # + kern.bias(Q) # k = kern.RBF(Q, ARD=True, lengthscale=10.) - m = SSGPLVM(Y, Q, init="pca", num_inducing=num_inducing, kernel=k) + m = SSGPLVM(Y, Q, init="rand", num_inducing=num_inducing, kernel=k, group_spike=True) m.X.variance[:] = _np.random.uniform(0, .01, m.X.shape) - m.likelihood.variance = .1 + m.likelihood.variance = .01 if optimize: print("Optimizing model:") diff --git a/GPy/models/ss_gplvm.py b/GPy/models/ss_gplvm.py index c2b7c0d0..64d0fd5e 100644 --- a/GPy/models/ss_gplvm.py +++ b/GPy/models/ss_gplvm.py @@ -7,7 +7,7 @@ from ..core.sparse_gp_mpi import SparseGP_MPI from .. import kern from ..core.parameterization import Param from ..likelihoods import Gaussian -from ..core.parameterization.variational import SpikeAndSlabPrior, SpikeAndSlabPosterior +from ..core.parameterization.variational import SpikeAndSlabPrior, SpikeAndSlabPosterior,VariationalPrior from ..inference.latent_function_inference.var_dtc_parallel import update_gradients, VarDTC_minibatch from ..kern._src.psi_comp.ssrbf_psi_gpucomp import PSICOMP_SSRBF_GPU @@ -15,13 +15,13 @@ class IBPPosterior(SpikeAndSlabPosterior): ''' The SpikeAndSlab distribution for variational approximations. ''' - def __init__(self, means, variances, binary_prob, tau, name='latent space'): + def __init__(self, means, variances, binary_prob, tau=None, name='latent space'): """ binary_prob : the probability of the distribution on the slab part. """ - from ..core.parameterization.transformations import Logexp, __fixed__ - super(IBPPosterior, self).__init__(means, variances, name) - self.tau = Param("tau",SpikeAndSlabPosterior, Logexp) + from ..core.parameterization.transformations import Logexp + super(IBPPosterior, self).__init__(means, variances, binary_prob, group_spike=True, name=name) + self.tau = Param("tau_", np.ones((self.gamma_group.shape[0],2)), Logexp()) self.link_parameter(self.tau) def set_gradients(self, grad): @@ -35,7 +35,7 @@ class IBPPosterior(SpikeAndSlabPosterior): dc['mean'] = self.mean[s] dc['variance'] = self.variance[s] dc['binary_prob'] = self.binary_prob[s] - dc['tau'] = self.tau[s] + dc['tau'] = self.tau dc['parameters'] = copy.copy(self.parameters) n.__dict__.update(dc) n.parameters[dc['mean']._parent_index_] = dc['mean'] @@ -53,16 +53,17 @@ class IBPPosterior(SpikeAndSlabPosterior): else: return super(IBPPosterior, self).__getitem__(s) -class IBPPrior(SpikeAndSlabPrior): +class IBPPrior(VariationalPrior): def __init__(self, input_dim, alpha =2., name='IBPPrior', **kw): - super(SpikeAndSlabPrior, self).__init__(name=name, **kw) + super(IBPPrior, self).__init__(name=name, **kw) from ..core.parameterization.transformations import Logexp, __fixed__ self.input_dim = input_dim + self.variance = 1. self.alpha = Param('alpha', alpha, __fixed__) self.link_parameter(self.alpha) def KL_divergence(self, variational_posterior): - mu, S, gamma, tau = variational_posterior.mean.values, variational_posterior.variance.values, variational_posterior.gamma.values, variational_posterior.tau.values + mu, S, gamma, tau = variational_posterior.mean.values, variational_posterior.variance.values, variational_posterior.gamma_group.values, variational_posterior.tau.values var_mean = np.square(mu)/self.variance var_S = (S/self.variance - np.log(S)) @@ -77,18 +78,17 @@ class IBPPrior(SpikeAndSlabPrior): return part1+part2 def update_gradients_KL(self, variational_posterior): - mu, S, gamma, tau = variational_posterior.mean.values, variational_posterior.variance.values, variational_posterior.gamma.values, variational_posterior.tau.values + mu, S, gamma, tau = variational_posterior.mean.values, variational_posterior.variance.values, variational_posterior.gamma_group.values, variational_posterior.tau.values - variational_posterior.binary_prob.gradient -= ((np.square(mu)+S)/self.variance-np.log(S)+np.log(self.variance)-1.)/2. - mu.gradient -= gamma*mu/self.variance - S.gradient -= (1./self.variance - 1./S) * gamma /2. - if self.learnPi: - if len(self.pi)==1: - self.pi.gradient = (gamma/self.pi - (1.-gamma)/(1.-self.pi)).sum() - elif len(self.pi.shape)==1: - self.pi.gradient = (gamma/self.pi - (1.-gamma)/(1.-self.pi)).sum(axis=0) - else: - self.pi[idx].gradient = (gamma/self.pi[idx] - (1.-gamma)/(1.-self.pi[idx])) + variational_posterior.mean.gradient -= gamma*mu/self.variance + variational_posterior.variance.gradient -= (1./self.variance - 1./S) * gamma /2. + from scipy.special import digamma,polygamma + dgamma = (np.log(gamma/(1.-gamma))+ digamma(tau[:,1])-digamma(tau[:,0]))/mu.shape[0] + variational_posterior.binary_prob.gradient -= dgamma+((np.square(mu)+S)/self.variance-np.log(S)+np.log(self.variance)-1.)/2. + ad = self.alpha/self.input_dim + common = (ad+2-tau[:,0]-tau[:,1])*polygamma(1,tau.sum(axis=1)) + variational_posterior.tau.gradient[:,0] = -((tau[:,0]-gamma-ad)*polygamma(1,tau[:,0])+common) + variational_posterior.tau.gradient[:,1] = -((tau[:,1]+gamma-2)*polygamma(1,tau[:,1])+common) class SSGPLVM(SparseGP_MPI): """ @@ -103,7 +103,7 @@ class SSGPLVM(SparseGP_MPI): """ def __init__(self, Y, input_dim, X=None, X_variance=None, Gamma=None, init='PCA', num_inducing=10, - Z=None, kernel=None, inference_method=None, likelihood=None, name='Spike_and_Slab GPLVM', group_spike=False, mpi_comm=None, pi=None, learnPi=False,normalizer=False, **kwargs): + Z=None, kernel=None, inference_method=None, likelihood=None, name='Spike_and_Slab GPLVM', group_spike=False, IBP=False, alpha=2., tau=None, mpi_comm=None, pi=None, learnPi=False,normalizer=False, **kwargs): self.group_spike = group_spike @@ -144,10 +144,14 @@ class SSGPLVM(SparseGP_MPI): if pi is None: pi = np.empty((input_dim)) pi[:] = 0.5 - self.variational_prior = SpikeAndSlabPrior(pi=pi,learnPi=learnPi, group_spike=group_spike) # the prior probability of the latent binary variable b - - X = SpikeAndSlabPosterior(X, X_variance, gamma, group_spike=group_spike) - + + if IBP: + self.variational_prior = IBPPrior(input_dim=input_dim, alpha=alpha) + X = IBPPosterior(X, X_variance, gamma, tau=tau) + else: + self.variational_prior = SpikeAndSlabPrior(pi=pi,learnPi=learnPi, group_spike=group_spike) # the prior probability of the latent binary variable b + X = SpikeAndSlabPosterior(X, X_variance, gamma, group_spike=group_spike) + super(SSGPLVM,self).__init__(X, Y, Z, kernel, likelihood, variational_prior=self.variational_prior, inference_method=inference_method, name=name, mpi_comm=mpi_comm, normalizer=normalizer, **kwargs) self.link_parameter(self.X, index=0) From d3e79495e74729b2e3352c0b2d62615e5e3618d2 Mon Sep 17 00:00:00 2001 From: Alan Saul Date: Thu, 21 May 2015 16:33:35 +0100 Subject: [PATCH 22/41] Added option for plotting with SVGP --- GPy/plotting/matplot_dep/models_plots.py | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) diff --git a/GPy/plotting/matplot_dep/models_plots.py b/GPy/plotting/matplot_dep/models_plots.py index 16568c7d..77c42825 100644 --- a/GPy/plotting/matplot_dep/models_plots.py +++ b/GPy/plotting/matplot_dep/models_plots.py @@ -11,6 +11,7 @@ from base_plots import gpplot, x_frame1D, x_frame2D from ...models.gp_coregionalized_regression import GPCoregionalizedRegression from ...models.sparse_gp_coregionalized_regression import SparseGPCoregionalizedRegression from scipy import sparse +from ...core.parameterization.variational import VariationalPosterior def plot_fit(model, plot_limits=None, which_data_rows='all', which_data_ycols='all', fixed_inputs=[], @@ -78,7 +79,7 @@ def plot_fit(model, plot_limits=None, which_data_rows='all', if predict_kw is None: predict_kw = {} - + #work out what the inputs are for plotting (1D or 2D) fixed_dims = np.array([i for i,v in fixed_inputs]) free_dims = np.setdiff1d(np.arange(model.input_dim),fixed_dims) @@ -219,7 +220,7 @@ def plot_fit_f(model, *args, **kwargs): kwargs['plot_raw'] = True plot_fit(model,*args, **kwargs) -def fixed_inputs(model, non_fixed_inputs, fix_routine='median', as_list=True): +def fixed_inputs(model, non_fixed_inputs, fix_routine='median', as_list=True, X_all=False): """ Convenience function for returning back fixed_inputs where the other inputs are fixed using fix_routine @@ -235,8 +236,13 @@ def fixed_inputs(model, non_fixed_inputs, fix_routine='median', as_list=True): f_inputs = [] if hasattr(model, 'has_uncertain_inputs') and model.has_uncertain_inputs(): X = model.X.mean.values.copy() - else: + elif isinstance(model.X, VariationalPosterior): X = model.X.values.copy() + else: + if X_all: + X = model.X_all.copy() + else: + X = model.X.copy() for i in range(X.shape[1]): if i not in non_fixed_inputs: if fix_routine == 'mean': From b5cac9af8ca48531a1a03180f418cfcea2f30e3a Mon Sep 17 00:00:00 2001 From: Zhenwen Dai Date: Fri, 22 May 2015 14:29:53 +0100 Subject: [PATCH 23/41] [ssmrd] implement with IBP prior --- GPy/core/parameterization/variational.py | 10 +- GPy/models/ss_gplvm.py | 26 ++- GPy/models/ss_mrd.py | 253 +++++++++++++++++++++-- 3 files changed, 262 insertions(+), 27 deletions(-) diff --git a/GPy/core/parameterization/variational.py b/GPy/core/parameterization/variational.py index 16192845..7a58ac5e 100644 --- a/GPy/core/parameterization/variational.py +++ b/GPy/core/parameterization/variational.py @@ -80,7 +80,7 @@ class SpikeAndSlabPrior(VariationalPrior): pi = self.pi if self.group_spike: - dgamma = np.log((1-pi)/pi*gamma/(1.-gamma))/mu.shape[0] + dgamma = np.log((1-pi)/pi*gamma/(1.-gamma))/variational_posterior.num_data else: dgamma = np.log((1-pi)/pi*gamma/(1.-gamma)) variational_posterior.binary_prob.gradient -= dgamma+((np.square(mu)+S)/self.variance-np.log(S)+np.log(self.variance)-1.)/2. @@ -165,12 +165,16 @@ class SpikeAndSlabPosterior(VariationalPosterior): ''' The SpikeAndSlab distribution for variational approximations. ''' - def __init__(self, means, variances, binary_prob, group_spike=False, name='latent space'): + def __init__(self, means, variances, binary_prob, group_spike=False, sharedX=False, name='latent space'): """ binary_prob : the probability of the distribution on the slab part. """ super(SpikeAndSlabPosterior, self).__init__(means, variances, name) self.group_spike = group_spike + self.sharedX = sharedX + if sharedX: + self.mean.fix(warning=False) + self.variance.fix(warning=False) if group_spike: self.gamma_group = Param("binary_prob_group",binary_prob.mean(axis=0),Logistic(1e-6,1.-1e-6)) self.gamma = Param("binary_prob",binary_prob, __fixed__) @@ -181,7 +185,7 @@ class SpikeAndSlabPosterior(VariationalPosterior): def propogate_val(self): if self.group_spike: - self.gamma.param_array.values.reshape(self.gamma.shape)[:] = self.gamma_group.values + self.gamma.values[:] = self.gamma_group.values def collate_gradient(self): if self.group_spike: diff --git a/GPy/models/ss_gplvm.py b/GPy/models/ss_gplvm.py index 64d0fd5e..3e2aa552 100644 --- a/GPy/models/ss_gplvm.py +++ b/GPy/models/ss_gplvm.py @@ -15,12 +15,16 @@ class IBPPosterior(SpikeAndSlabPosterior): ''' The SpikeAndSlab distribution for variational approximations. ''' - def __init__(self, means, variances, binary_prob, tau=None, name='latent space'): + def __init__(self, means, variances, binary_prob, tau=None, sharedX=False, name='latent space'): """ binary_prob : the probability of the distribution on the slab part. """ from ..core.parameterization.transformations import Logexp super(IBPPosterior, self).__init__(means, variances, binary_prob, group_spike=True, name=name) + self.sharedX = sharedX + if sharedX: + self.mean.fix(warning=False) + self.variance.fix(warning=False) self.tau = Param("tau_", np.ones((self.gamma_group.shape[0],2)), Logexp()) self.link_parameter(self.tau) @@ -83,7 +87,7 @@ class IBPPrior(VariationalPrior): variational_posterior.mean.gradient -= gamma*mu/self.variance variational_posterior.variance.gradient -= (1./self.variance - 1./S) * gamma /2. from scipy.special import digamma,polygamma - dgamma = (np.log(gamma/(1.-gamma))+ digamma(tau[:,1])-digamma(tau[:,0]))/mu.shape[0] + dgamma = (np.log(gamma/(1.-gamma))+ digamma(tau[:,1])-digamma(tau[:,0]))/variational_posterior.num_data variational_posterior.binary_prob.gradient -= dgamma+((np.square(mu)+S)/self.variance-np.log(S)+np.log(self.variance)-1.)/2. ad = self.alpha/self.input_dim common = (ad+2-tau[:,0]-tau[:,1])*polygamma(1,tau.sum(axis=1)) @@ -103,9 +107,11 @@ class SSGPLVM(SparseGP_MPI): """ def __init__(self, Y, input_dim, X=None, X_variance=None, Gamma=None, init='PCA', num_inducing=10, - Z=None, kernel=None, inference_method=None, likelihood=None, name='Spike_and_Slab GPLVM', group_spike=False, IBP=False, alpha=2., tau=None, mpi_comm=None, pi=None, learnPi=False,normalizer=False, **kwargs): + Z=None, kernel=None, inference_method=None, likelihood=None, name='Spike_and_Slab GPLVM', group_spike=False, IBP=False, alpha=2., tau=None, mpi_comm=None, pi=None, learnPi=False,normalizer=False, sharedX=False, variational_prior=None,**kwargs): self.group_spike = group_spike + self.init = init + self.sharedX = sharedX if X == None: from ..util.initialization import initialize_latent @@ -113,8 +119,6 @@ class SSGPLVM(SparseGP_MPI): else: fracs = np.ones(input_dim) - self.init = init - if X_variance is None: # The variance of the variational approximation (S) X_variance = np.random.uniform(0,.1,X.shape) @@ -146,11 +150,11 @@ class SSGPLVM(SparseGP_MPI): pi[:] = 0.5 if IBP: - self.variational_prior = IBPPrior(input_dim=input_dim, alpha=alpha) - X = IBPPosterior(X, X_variance, gamma, tau=tau) + self.variational_prior = IBPPrior(input_dim=input_dim, alpha=alpha) if variational_prior is None else variational_prior + X = IBPPosterior(X, X_variance, gamma, tau=tau,sharedX=sharedX) else: - self.variational_prior = SpikeAndSlabPrior(pi=pi,learnPi=learnPi, group_spike=group_spike) # the prior probability of the latent binary variable b - X = SpikeAndSlabPosterior(X, X_variance, gamma, group_spike=group_spike) + self.variational_prior = SpikeAndSlabPrior(pi=pi,learnPi=learnPi, group_spike=group_spike) if variational_prior is None else variational_prior + X = SpikeAndSlabPosterior(X, X_variance, gamma, group_spike=group_spike,sharedX=sharedX) super(SSGPLVM,self).__init__(X, Y, Z, kernel, likelihood, variational_prior=self.variational_prior, inference_method=inference_method, name=name, mpi_comm=mpi_comm, normalizer=normalizer, **kwargs) self.link_parameter(self.X, index=0) @@ -163,8 +167,12 @@ class SSGPLVM(SparseGP_MPI): """Get the gradients of the posterior distribution of X in its specific form.""" return X.mean.gradient, X.variance.gradient, X.binary_prob.gradient + def _propogate_X_val(self): + pass + def parameters_changed(self): self.X.propogate_val() + if self.sharedX: self._highest_parent_._propogate_X_val() super(SSGPLVM,self).parameters_changed() if isinstance(self.inference_method, VarDTC_minibatch): self.X.collate_gradient() diff --git a/GPy/models/ss_mrd.py b/GPy/models/ss_mrd.py index bd2efce0..41289d3f 100644 --- a/GPy/models/ss_mrd.py +++ b/GPy/models/ss_mrd.py @@ -2,33 +2,256 @@ The Maniforld Relevance Determination model with the spike-and-slab prior """ +import numpy as np from ..core import Model from .ss_gplvm import SSGPLVM +from ..core.parameterization.variational import SpikeAndSlabPrior,NormalPosterior,VariationalPrior +from ..util.misc import param_to_array +from ..kern import RBF +from ..core import Param +from numpy.linalg.linalg import LinAlgError class SSMRD(Model): - def __init__(self, Ylist, input_dim, X=None, X_variance=None, - initx = 'PCA', initz = 'permute', - num_inducing=10, Z=None, kernel=None, - inference_method=None, likelihoods=None, name='ss_mrd', Ynames=None): + def __init__(self, Ylist, input_dim, X=None, X_variance=None, Gammas=None, initx = 'PCA_concat', initz = 'permute', + num_inducing=10, Zs=None, kernels=None, inference_methods=None, likelihoods=None, group_spike=True, + pi=0.5, name='ss_mrd', Ynames=None, mpi_comm=None, IBP=False, alpha=2., taus=None, ): super(SSMRD, self).__init__(name) + self.mpi_comm = mpi_comm + self._PROPAGATE_ = False - self.updates = False - self.models = [SSGPLVM(y, input_dim, X=X, X_variance=X_variance, num_inducing=num_inducing,Z=Z,init=initx, - kernel=kernel.copy() if kernel else None,inference_method=inference_method,likelihood=likelihoods, - name='model_'+str(i)) for i,y in enumerate(Ylist)] - self.add_parameters(*(self.models)) + # initialize X for individual models + X, X_variance, Gammas, fracs = self._init_X(Ylist, input_dim, X, X_variance, Gammas, initx) + self.X = NormalPosterior(means=X, variances=X_variance) - [[[self.models[m].X.mean[i,j:j+1].tie('mean_'+str(i)+'_'+str(j)) for m in range(len(self.models))] for j in range(self.models[0].X.mean.shape[1])] - for i in range(self.models[0].X.mean.shape[0])] - [[[self.models[m].X.variance[i,j:j+1].tie('var_'+str(i)+'_'+str(j)) for m in range(len(self.models))] for j in range(self.models[0].X.variance.shape[1])] - for i in range(self.models[0].X.variance.shape[0])] + if kernels is None: + kernels = [RBF(input_dim, lengthscale=1./fracs, ARD=True) for i in xrange(len(Ylist))] + if Zs is None: + Zs = [None]* len(Ylist) + if likelihoods is None: + likelihoods = [None]* len(Ylist) + if inference_methods is None: + inference_methods = [None]* len(Ylist) - self.updates = True + if IBP: + self.var_priors = [IBPPrior_SSMRD(len(Ylist),input_dim,alpha=alpha) for i in xrange(len(Ylist))] + else: + self.var_priors = [SpikeAndSlabPrior_SSMRD(nModels=len(Ylist),pi=pi,learnPi=False, group_spike=group_spike) for i in xrange(len(Ylist))] + self.models = [SSGPLVM(y, input_dim, X=X.copy(), X_variance=X_variance.copy(), Gamma=Gammas[i], num_inducing=num_inducing,Z=Zs[i], learnPi=False, group_spike=group_spike, + kernel=kernels[i],inference_method=inference_methods[i],likelihood=likelihoods[i], variational_prior=self.var_priors[i], IBP=IBP, tau=None if taus is None else taus[i], + name='model_'+str(i), mpi_comm=mpi_comm, sharedX=True) for i,y in enumerate(Ylist)] + self.link_parameters(*(self.models+[self.X])) + + def _propogate_X_val(self): + if self._PROPAGATE_: return + for m in self.models: + m.X.mean.values[:] = self.X.mean.values + m.X.variance.values[:] = self.X.variance.values + varp_list = [m.X for m in self.models] + [vp._update_inernal(varp_list) for vp in self.var_priors] + self._PROPAGATE_=True + + def _collate_X_gradient(self): + self._PROPAGATE_ = False + self.X.mean.gradient[:] = 0 + self.X.variance.gradient[:] = 0 + for m in self.models: + self.X.mean.gradient += m.X.mean.gradient + self.X.variance.gradient += m.X.variance.gradient def parameters_changed(self): - super(SSMRD, self).parameters_changed() + super(SSMRD, self).parameters_changed() + [m.parameters_changed() for m in self.models] self._log_marginal_likelihood = sum([m._log_marginal_likelihood for m in self.models]) + self._collate_X_gradient() def log_likelihood(self): return self._log_marginal_likelihood + + def _init_X(self, Ylist, input_dim, X=None, X_variance=None, Gammas=None, initx='PCA_concat'): + + # Divide latent dimensions + idx = np.empty((input_dim,),dtype=np.int) + residue = (input_dim)%(len(Ylist)) + for i in xrange(len(Ylist)): + if i < residue: + size = input_dim/len(Ylist)+1 + idx[i*size:(i+1)*size] = i + else: + size = input_dim/len(Ylist) + idx[i*size+residue:(i+1)*size+residue] = i + + if X is None: + if initx == 'PCA_concat': + X = np.empty((Ylist[0].shape[0],input_dim)) + fracs = np.empty((input_dim,)) + from ..util.initialization import initialize_latent + for i in xrange(len(Ylist)): + Y = Ylist[i] + dim = (idx==i).sum() + if dim>0: + x, fr = initialize_latent('PCA', dim, Y) + X[:,idx==i] = x + fracs[idx==i] = fr + elif initx=='PCA_joint': + y = np.hstack(Ylist) + from ..util.initialization import initialize_latent + X, fracs = initialize_latent('PCA', input_dim, y) + else: + X = np.random.randn(Ylist[0].shape[0], input_dim) + fracs = np.ones(input_dim) + else: + fracs = np.ones(input_dim) + + + if X_variance is None: # The variance of the variational approximation (S) + X_variance = np.random.uniform(0,.1,X.shape) + + if Gammas is None: + Gammas = [] + for x in X: + gamma = np.empty_like(X) # The posterior probabilities of the binary variable in the variational approximation + gamma[:] = 0.5 + 0.1 * np.random.randn(X.shape[0], input_dim) + gamma[gamma>1.-1e-9] = 1.-1e-9 + gamma[gamma<1e-9] = 1e-9 + Gammas.append(gamma) + return X, X_variance, Gammas, fracs + + @Model.optimizer_array.setter + def optimizer_array(self, p): + if self.mpi_comm != None: + if self._IN_OPTIMIZATION_ and self.mpi_comm.rank==0: + self.mpi_comm.Bcast(np.int32(1),root=0) + self.mpi_comm.Bcast(p, root=0) + Model.optimizer_array.fset(self,p) + + def optimize(self, optimizer=None, start=None, **kwargs): + self._IN_OPTIMIZATION_ = True + if self.mpi_comm==None: + super(SSMRD, self).optimize(optimizer,start,**kwargs) + elif self.mpi_comm.rank==0: + super(SSMRD, self).optimize(optimizer,start,**kwargs) + self.mpi_comm.Bcast(np.int32(-1),root=0) + elif self.mpi_comm.rank>0: + x = self.optimizer_array.copy() + flag = np.empty(1,dtype=np.int32) + while True: + self.mpi_comm.Bcast(flag,root=0) + if flag==1: + try: + self.optimizer_array = x + self._fail_count = 0 + except (LinAlgError, ZeroDivisionError, ValueError): + if self._fail_count >= self._allowed_failures: + raise + self._fail_count += 1 + elif flag==-1: + break + else: + self._IN_OPTIMIZATION_ = False + raise Exception("Unrecognizable flag for synchronization!") + self._IN_OPTIMIZATION_ = False + + +class SpikeAndSlabPrior_SSMRD(SpikeAndSlabPrior): + def __init__(self, nModels, pi=0.5, learnPi=False, group_spike=True, variance = 1.0, name='SSMRDPrior', **kw): + self.nModels = nModels + self._b_prob_all = 0.5 + super(SpikeAndSlabPrior_SSMRD, self).__init__(pi=pi,learnPi=learnPi,group_spike=group_spike,variance=variance, name=name, **kw) + + def _update_inernal(self, varp_list): + """Make an update of the internal status by gathering the variational posteriors for all the individual models.""" + # The probability for the binary variable for the same latent dimension of any of the models is on. + if self.group_spike: + self._b_prob_all = 1.-param_to_array(varp_list[0].gamma_group) + [np.multiply(self._b_prob_all, 1.-vp.gamma_group, self._b_prob_all) for vp in varp_list[1:]] + else: + self._b_prob_all = 1.-param_to_array(varp_list[0].binary_prob) + [np.multiply(self._b_prob_all, 1.-vp.binary_prob, self._b_prob_all) for vp in varp_list[1:]] + + def KL_divergence(self, variational_posterior): + mu = variational_posterior.mean + S = variational_posterior.variance + if self.group_spike: + gamma = variational_posterior.binary_prob[0] + else: + gamma = variational_posterior.binary_prob + if len(self.pi.shape)==2: + idx = np.unique(gamma._raveled_index()/gamma.shape[-1]) + pi = self.pi[idx] + else: + pi = self.pi + + var_mean = np.square(mu)/self.variance + var_S = (S/self.variance - np.log(S)) + var_gamma = (gamma*np.log(gamma/pi)).sum()+((1-gamma)*np.log((1-gamma)/(1-pi))).sum() + return var_gamma +((1.-self._b_prob_all)*(np.log(self.variance)-1. +var_mean + var_S)).sum()/(2.*self.nModels) + + def update_gradients_KL(self, variational_posterior): + mu = variational_posterior.mean + S = variational_posterior.variance + N = variational_posterior.num_data + if self.group_spike: + gamma = variational_posterior.binary_prob.values[0] + else: + gamma = variational_posterior.binary_prob.values + if len(self.pi.shape)==2: + idx = np.unique(gamma._raveled_index()/gamma.shape[-1]) + pi = self.pi[idx] + else: + pi = self.pi + + if self.group_spike: + tmp = self._b_prob_all/(1.-gamma) + variational_posterior.binary_prob.gradient -= np.log((1-pi)/pi*gamma/(1.-gamma))/N +tmp*((np.square(mu)+S)/self.variance-np.log(S)+np.log(self.variance)-1.)/2. + else: + variational_posterior.binary_prob.gradient -= np.log((1-pi)/pi*gamma/(1.-gamma))+((np.square(mu)+S)/self.variance-np.log(S)+np.log(self.variance)-1.)/2. + mu.gradient -= (1.-self._b_prob_all)*mu/(self.variance*self.nModels) + S.gradient -= (1./self.variance - 1./S) * (1.-self._b_prob_all) /(2.*self.nModels) + if self.learnPi: + raise 'Not Supported!' + +class IBPPrior_SSMRD(VariationalPrior): + def __init__(self, nModels, input_dim, alpha =2., tau=None, name='IBPPrior', **kw): + super(IBPPrior_SSMRD, self).__init__(name=name, **kw) + from ..core.parameterization.transformations import Logexp, __fixed__ + self.nModels = nModels + self._b_prob_all = 0.5 + self.input_dim = input_dim + self.variance = 1. + self.alpha = Param('alpha', alpha, __fixed__) + self.link_parameter(self.alpha) + + def _update_inernal(self, varp_list): + """Make an update of the internal status by gathering the variational posteriors for all the individual models.""" + # The probability for the binary variable for the same latent dimension of any of the models is on. + self._b_prob_all = 1.-param_to_array(varp_list[0].gamma_group) + [np.multiply(self._b_prob_all, 1.-vp.gamma_group, self._b_prob_all) for vp in varp_list[1:]] + + def KL_divergence(self, variational_posterior): + mu, S, gamma, tau = variational_posterior.mean.values, variational_posterior.variance.values, variational_posterior.gamma_group.values, variational_posterior.tau.values + + var_mean = np.square(mu)/self.variance + var_S = (S/self.variance - np.log(S)) + part1 = ((1.-self._b_prob_all)* (np.log(self.variance)-1. +var_mean + var_S)).sum()/(2.*self.nModels) + + ad = self.alpha/self.input_dim + from scipy.special import betaln,digamma + part2 = (gamma*np.log(gamma)).sum() + ((1.-gamma)*np.log(1.-gamma)).sum() + (betaln(ad,1.)*self.input_dim -betaln(tau[:,0], tau[:,1]).sum())/self.nModels \ + + (( (tau[:,0]-ad)/self.nModels -gamma)*digamma(tau[:,0])).sum() + \ + (((tau[:,1]-1.)/self.nModels+gamma-1.)*digamma(tau[:,1])).sum() + (((1.+ad-tau[:,0]-tau[:,1])/self.nModels+1.)*digamma(tau.sum(axis=1))).sum() + return part1+part2 + + def update_gradients_KL(self, variational_posterior): + mu, S, gamma, tau = variational_posterior.mean.values, variational_posterior.variance.values, variational_posterior.gamma_group.values, variational_posterior.tau.values + + variational_posterior.mean.gradient -= (1.-self._b_prob_all)*mu/(self.variance*self.nModels) + variational_posterior.variance.gradient -= (1./self.variance - 1./S) * (1.-self._b_prob_all) /(2.*self.nModels) + from scipy.special import digamma,polygamma + tmp = self._b_prob_all/(1.-gamma) + dgamma = (np.log(gamma/(1.-gamma))+ digamma(tau[:,1])-digamma(tau[:,0]))/variational_posterior.num_data + variational_posterior.binary_prob.gradient -= dgamma+tmp*((np.square(mu)+S)/self.variance-np.log(S)+np.log(self.variance)-1.)/2. + ad = self.alpha/self.input_dim + common = ((1.+ad-tau[:,0]-tau[:,1])/self.nModels+1.)*polygamma(1,tau.sum(axis=1)) + variational_posterior.tau.gradient[:,0] = -(((tau[:,0]-ad)/self.nModels -gamma)*polygamma(1,tau[:,0])+common) + variational_posterior.tau.gradient[:,1] = -(((tau[:,1]-1.)/self.nModels+gamma-1.)*polygamma(1,tau[:,1])+common) From 56d50e0469e3ef0c530d560ce2bfca59f5e23591 Mon Sep 17 00:00:00 2001 From: Alan Saul Date: Fri, 22 May 2015 21:16:38 +0100 Subject: [PATCH 24/41] Reshaped log predictive density to have D outputs --- GPy/likelihoods/likelihood.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/GPy/likelihoods/likelihood.py b/GPy/likelihoods/likelihood.py index 7a6721f9..31f5dffd 100644 --- a/GPy/likelihoods/likelihood.py +++ b/GPy/likelihoods/likelihood.py @@ -143,7 +143,7 @@ class Likelihood(Parameterized): p_ystar, _ = zip(*[quad(integral_generator(yi, mi, vi, yi_m), -np.inf, np.inf) for yi, mi, vi, yi_m in zipped_values]) - p_ystar = np.array(p_ystar).reshape(-1, 1) + p_ystar = np.array(p_ystar).reshape(*y_test.shape) return np.log(p_ystar) def log_predictive_density_sampling(self, y_test, mu_star, var_star, Y_metadata=None, num_samples=1000): @@ -173,6 +173,7 @@ class Likelihood(Parameterized): from scipy.misc import logsumexp log_p_ystar = -np.log(num_samples) + logsumexp(self.logpdf(fi_samples, y_test, Y_metadata=Y_metadata), axis=1) + log_p_ystar = np.array(log_p_ystar).reshape(*y_test.shape) return log_p_ystar From 50f656c7b5166ea981762a2306b120603b7fc44b Mon Sep 17 00:00:00 2001 From: Alan Saul Date: Tue, 26 May 2015 16:02:27 +0100 Subject: [PATCH 25/41] Updated plotting --- GPy/plotting/matplot_dep/models_plots.py | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) diff --git a/GPy/plotting/matplot_dep/models_plots.py b/GPy/plotting/matplot_dep/models_plots.py index 16568c7d..77c42825 100644 --- a/GPy/plotting/matplot_dep/models_plots.py +++ b/GPy/plotting/matplot_dep/models_plots.py @@ -11,6 +11,7 @@ from base_plots import gpplot, x_frame1D, x_frame2D from ...models.gp_coregionalized_regression import GPCoregionalizedRegression from ...models.sparse_gp_coregionalized_regression import SparseGPCoregionalizedRegression from scipy import sparse +from ...core.parameterization.variational import VariationalPosterior def plot_fit(model, plot_limits=None, which_data_rows='all', which_data_ycols='all', fixed_inputs=[], @@ -78,7 +79,7 @@ def plot_fit(model, plot_limits=None, which_data_rows='all', if predict_kw is None: predict_kw = {} - + #work out what the inputs are for plotting (1D or 2D) fixed_dims = np.array([i for i,v in fixed_inputs]) free_dims = np.setdiff1d(np.arange(model.input_dim),fixed_dims) @@ -219,7 +220,7 @@ def plot_fit_f(model, *args, **kwargs): kwargs['plot_raw'] = True plot_fit(model,*args, **kwargs) -def fixed_inputs(model, non_fixed_inputs, fix_routine='median', as_list=True): +def fixed_inputs(model, non_fixed_inputs, fix_routine='median', as_list=True, X_all=False): """ Convenience function for returning back fixed_inputs where the other inputs are fixed using fix_routine @@ -235,8 +236,13 @@ def fixed_inputs(model, non_fixed_inputs, fix_routine='median', as_list=True): f_inputs = [] if hasattr(model, 'has_uncertain_inputs') and model.has_uncertain_inputs(): X = model.X.mean.values.copy() - else: + elif isinstance(model.X, VariationalPosterior): X = model.X.values.copy() + else: + if X_all: + X = model.X_all.copy() + else: + X = model.X.copy() for i in range(X.shape[1]): if i not in non_fixed_inputs: if fix_routine == 'mean': From 3341b3c56a4737c1861648828613dc4e1d777d83 Mon Sep 17 00:00:00 2001 From: James Hensman Date: Wed, 27 May 2015 12:29:53 +0100 Subject: [PATCH 26/41] minor bugfix in raw_predict with full_cov for sparseGP --- GPy/core/sparse_gp.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/core/sparse_gp.py b/GPy/core/sparse_gp.py index 0c5e1dd2..c7c99be6 100644 --- a/GPy/core/sparse_gp.py +++ b/GPy/core/sparse_gp.py @@ -133,7 +133,7 @@ class SparseGP(GP): var = Kxx - np.dot(Kx.T, np.dot(self.posterior.woodbury_inv, Kx)) elif self.posterior.woodbury_inv.ndim == 3: var = np.empty((Kxx.shape[0],Kxx.shape[1],self.posterior.woodbury_inv.shape[2])) - for i in range(var.shape[1]): + for i in range(var.shape[2]): var[:, :, i] = (Kxx - mdot(Kx.T, self.posterior.woodbury_inv[:, :, i], Kx)) var = var else: From 01b501e078a2647c1c28dfd2e37107d57f1cd89b Mon Sep 17 00:00:00 2001 From: James Hensman Date: Thu, 28 May 2015 12:21:52 +0100 Subject: [PATCH 27/41] added log jacobian transofms for Exponent, Logexp --- GPy/core/parameterization/parameter_core.py | 42 ++++++++++------ GPy/core/parameterization/transformations.py | 50 +++++++++++++------- 2 files changed, 62 insertions(+), 30 deletions(-) diff --git a/GPy/core/parameterization/parameter_core.py b/GPy/core/parameterization/parameter_core.py index 1bc6a29e..5b8c8c61 100644 --- a/GPy/core/parameterization/parameter_core.py +++ b/GPy/core/parameterization/parameter_core.py @@ -430,23 +430,37 @@ class Indexable(Nameable, Updateable): def log_prior(self): """evaluate the prior""" - if self.priors.size > 0: - x = self.param_array - #py3 fix - #return reduce(lambda a, b: a + b, (p.lnpdf(x[ind]).sum() for p, ind in self.priors.iteritems()), 0) - return reduce(lambda a, b: a + b, (p.lnpdf(x[ind]).sum() for p, ind in self.priors.items()), 0) - return 0. + if self.priors.size == 0: + return 0. + x = self.param_array + #evaluate the prior log densities + log_p = reduce(lambda a, b: a + b, (p.lnpdf(x[ind]).sum() for p, ind in self.priors.items()), 0) + #account for the transformation by evaluating the log Jacobian (where things are transformed) + log_j = 0. + priored_indexes = np.hstack([i for p, i in self.priors.items()]) + for c,j in self.constraints.items(): + for jj in j: + if jj in priored_indexes: + log_j += c.log_jacobian(x[jj]) + return log_p + log_j + + def _log_prior_gradients(self): """evaluate the gradients of the priors""" - if self.priors.size > 0: - x = self.param_array - ret = np.zeros(x.size) - #py3 fix - #[np.put(ret, ind, p.lnpdf_grad(x[ind])) for p, ind in self.priors.iteritems()] - [np.put(ret, ind, p.lnpdf_grad(x[ind])) for p, ind in self.priors.items()] - return ret - return 0. + if self.priors.size == 0: + return 0. + x = self.param_array + ret = np.zeros(x.size) + #compute derivate of prior density + [np.put(ret, ind, p.lnpdf_grad(x[ind])) for p, ind in self.priors.items()] + #add in jacobian derivatives if transformed + priored_indexes = np.hstack([i for p, i in self.priors.items()]) + for c,j in self.constraints.items(): + for jj in j: + if jj in priored_indexes: + ret[jj] += c.log_jacobian_grad(x[jj]) + return ret #=========================================================================== # Tie parameters together diff --git a/GPy/core/parameterization/transformations.py b/GPy/core/parameterization/transformations.py index 7e15cee9..d53cb6c8 100644 --- a/GPy/core/parameterization/transformations.py +++ b/GPy/core/parameterization/transformations.py @@ -31,6 +31,16 @@ class Transformation(object): raise NotImplementedError def finv(self, model_param): raise NotImplementedError + def log_jacobian(self, model_param): + """ + compute the log of the jacobian of f, evaluated at f(x)= model_param + """ + raise NotImplementedError + def log_jacobian_grad(self, model_param): + """ + compute the drivative of the log of the jacobian of f, evaluated at f(x)= model_param + """ + raise NotImplementedError def gradfactor(self, model_param, dL_dmodel_param): """ df(opt_param)_dopt_param evaluated at self.f(opt_param)=model_param, times the gradient dL_dmodel_param, @@ -74,9 +84,33 @@ class Logexp(Transformation): if np.any(f < 0.): print("Warning: changing parameters to satisfy constraints") return np.abs(f) + def log_jacobian(self, model_param): + return np.where(model_param>_lim_val, model_param, np.log(np.exp(model_param+1e-20) - 1.)) - model_param + def log_jacobian_grad(self, model_param): + return 1./(np.exp(model_param)-1.) def __str__(self): return '+ve' +class Exponent(Transformation): + domain = _POSITIVE + def f(self, x): + return np.where(x<_lim_val, np.where(x>-_lim_val, np.exp(x), np.exp(-_lim_val)), np.exp(_lim_val)) + def finv(self, x): + return np.log(x) + def gradfactor(self, f, df): + return np.einsum('i,i->i', df, f) + def initialize(self, f): + if np.any(f < 0.): + print("Warning: changing parameters to satisfy constraints") + return np.abs(f) + def log_jacobian(self, model_param): + return np.log(model_param) + def log_jacobian_grad(self, model_param): + return 1./model_param + def __str__(self): + return '+ve' + + class NormalTheta(Transformation): "Do not use, not officially supported!" @@ -417,22 +451,6 @@ class LogexpClipped(Logexp): def __str__(self): return '+ve_c' -class Exponent(Transformation): - # TODO: can't allow this to go to zero, need to set a lower bound. Similar with negative Exponent below. See old MATLAB code. - domain = _POSITIVE - def f(self, x): - return np.where(x<_lim_val, np.where(x>-_lim_val, np.exp(x), np.exp(-_lim_val)), np.exp(_lim_val)) - def finv(self, x): - return np.log(x) - def gradfactor(self, f, df): - return np.einsum('i,i->i', df, f) - def initialize(self, f): - if np.any(f < 0.): - print("Warning: changing parameters to satisfy constraints") - return np.abs(f) - def __str__(self): - return '+ve' - class NegativeExponent(Exponent): domain = _NEGATIVE def f(self, x): From 6240f494f27752f3949311c77d97a3087513b0bf Mon Sep 17 00:00:00 2001 From: Zhenwen Dai Date: Thu, 28 May 2015 14:19:46 +0100 Subject: [PATCH 28/41] [ssgplvm] change the default gamma interval --- GPy/core/gp.py | 1 - GPy/core/parameterization/variational.py | 4 ++-- 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 89313ae2..898c7b58 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -89,7 +89,6 @@ class GP(Model): assert mean_function.output_dim == self.output_dim self.link_parameter(mean_function) - #find a sensible inference method logger.info("initializing inference method") if inference_method is None: diff --git a/GPy/core/parameterization/variational.py b/GPy/core/parameterization/variational.py index 7a58ac5e..f33e7715 100644 --- a/GPy/core/parameterization/variational.py +++ b/GPy/core/parameterization/variational.py @@ -176,11 +176,11 @@ class SpikeAndSlabPosterior(VariationalPosterior): self.mean.fix(warning=False) self.variance.fix(warning=False) if group_spike: - self.gamma_group = Param("binary_prob_group",binary_prob.mean(axis=0),Logistic(1e-6,1.-1e-6)) + self.gamma_group = Param("binary_prob_group",binary_prob.mean(axis=0),Logistic(1e-10,1.-1e-10)) self.gamma = Param("binary_prob",binary_prob, __fixed__) self.link_parameters(self.gamma_group,self.gamma) else: - self.gamma = Param("binary_prob",binary_prob,Logistic(1e-6,1.-1e-6)) + self.gamma = Param("binary_prob",binary_prob,Logistic(1e-10,1.-1e-10)) self.link_parameter(self.gamma) def propogate_val(self): From c0e045c0ab33af0b70b8756d89e17adf5f1629f3 Mon Sep 17 00:00:00 2001 From: Zhenwen Dai Date: Thu, 28 May 2015 17:05:09 +0100 Subject: [PATCH 29/41] allow to set color for the skeleton visualization --- GPy/plotting/matplot_dep/visualize.py | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/GPy/plotting/matplot_dep/visualize.py b/GPy/plotting/matplot_dep/visualize.py index b57b7dfc..6903c2d2 100644 --- a/GPy/plotting/matplot_dep/visualize.py +++ b/GPy/plotting/matplot_dep/visualize.py @@ -408,12 +408,13 @@ class mocap_data_show_vpython(vpython_show): class mocap_data_show(matplotlib_show): """Base class for visualizing motion capture data.""" - def __init__(self, vals, axes=None, connect=None): + def __init__(self, vals, axes=None, connect=None, color='b'): if axes==None: fig = plt.figure() axes = fig.add_subplot(111, projection='3d', aspect='equal') matplotlib_show.__init__(self, vals, axes) + self.color = color self.connect = connect self.process_values() self.initialize_axes() @@ -423,7 +424,7 @@ class mocap_data_show(matplotlib_show): self.axes.figure.canvas.draw() def draw_vertices(self): - self.points_handle = self.axes.scatter(self.vals[:, 0], self.vals[:, 1], self.vals[:, 2]) + self.points_handle = self.axes.scatter(self.vals[:, 0], self.vals[:, 1], self.vals[:, 2], color=self.color) def draw_edges(self): self.line_handle = [] @@ -442,7 +443,7 @@ class mocap_data_show(matplotlib_show): z.append(self.vals[i, 2]) z.append(self.vals[j, 2]) z.append(np.NaN) - self.line_handle = self.axes.plot(np.array(x), np.array(y), np.array(z), 'b-') + self.line_handle = self.axes.plot(np.array(x), np.array(y), np.array(z), '-', color=self.color) def modify(self, vals): self.vals = vals.copy() @@ -494,7 +495,7 @@ class stick_show(mocap_data_show): class skeleton_show(mocap_data_show): """data_show class for visualizing motion capture data encoded as a skeleton with angles.""" - def __init__(self, vals, skel, axes=None, padding=0): + def __init__(self, vals, skel, axes=None, padding=0, color='b'): """data_show class for visualizing motion capture data encoded as a skeleton with angles. :param vals: set of modeled angles to use for printing in the axis when it's first created. :type vals: np.array @@ -506,7 +507,7 @@ class skeleton_show(mocap_data_show): self.skel = skel self.padding = padding connect = skel.connection_matrix() - mocap_data_show.__init__(self, vals, axes=axes, connect=connect) + mocap_data_show.__init__(self, vals, axes=axes, connect=connect, color=color) def process_values(self): """Takes a set of angles and converts them to the x,y,z coordinates in the internal prepresentation of the class, ready for plotting. From 21ee8cd80aa2441e7184f5540f8adc563b1b49bc Mon Sep 17 00:00:00 2001 From: James Hensman Date: Thu, 28 May 2015 22:22:51 +0100 Subject: [PATCH 30/41] jacobian bugfix --- GPy/core/parameterization/parameter_core.py | 1 + 1 file changed, 1 insertion(+) diff --git a/GPy/core/parameterization/parameter_core.py b/GPy/core/parameterization/parameter_core.py index 5b8c8c61..3d674142 100644 --- a/GPy/core/parameterization/parameter_core.py +++ b/GPy/core/parameterization/parameter_core.py @@ -440,6 +440,7 @@ class Indexable(Nameable, Updateable): log_j = 0. priored_indexes = np.hstack([i for p, i in self.priors.items()]) for c,j in self.constraints.items(): + if c is 'fixed':continue for jj in j: if jj in priored_indexes: log_j += c.log_jacobian(x[jj]) From c4752c15649f8559cbcd722ea84737f712dcda24 Mon Sep 17 00:00:00 2001 From: James Hensman Date: Wed, 3 Jun 2015 21:23:27 +0100 Subject: [PATCH 31/41] Jacobians should not be computed only for transforms --- GPy/core/parameterization/parameter_core.py | 21 ++++++++++----------- 1 file changed, 10 insertions(+), 11 deletions(-) diff --git a/GPy/core/parameterization/parameter_core.py b/GPy/core/parameterization/parameter_core.py index 3d674142..067960ce 100644 --- a/GPy/core/parameterization/parameter_core.py +++ b/GPy/core/parameterization/parameter_core.py @@ -433,35 +433,34 @@ class Indexable(Nameable, Updateable): if self.priors.size == 0: return 0. x = self.param_array - #evaluate the prior log densities + #evaluate the prior log densities log_p = reduce(lambda a, b: a + b, (p.lnpdf(x[ind]).sum() for p, ind in self.priors.items()), 0) - #account for the transformation by evaluating the log Jacobian (where things are transformed) - log_j = 0. - priored_indexes = np.hstack([i for p, i in self.priors.items()]) + #account for the transformation by evaluating the log Jacobian (where things are transformed) + log_j = 0. + priored_indexes = np.hstack([i for p, i in self.priors.items()]) for c,j in self.constraints.items(): - if c is 'fixed':continue + if not isinstance(c, Transformation):continue for jj in j: if jj in priored_indexes: log_j += c.log_jacobian(x[jj]) - return log_p + log_j + return log_p + log_j - def _log_prior_gradients(self): """evaluate the gradients of the priors""" if self.priors.size == 0: return 0. x = self.param_array ret = np.zeros(x.size) - #compute derivate of prior density + #compute derivate of prior density [np.put(ret, ind, p.lnpdf_grad(x[ind])) for p, ind in self.priors.items()] - #add in jacobian derivatives if transformed - priored_indexes = np.hstack([i for p, i in self.priors.items()]) + #add in jacobian derivatives if transformed + priored_indexes = np.hstack([i for p, i in self.priors.items()]) for c,j in self.constraints.items(): for jj in j: if jj in priored_indexes: ret[jj] += c.log_jacobian_grad(x[jj]) - return ret + return ret #=========================================================================== # Tie parameters together From 451f145f88def704d090f346f642f28130becc13 Mon Sep 17 00:00:00 2001 From: James Hensman Date: Wed, 3 Jun 2015 21:27:17 +0100 Subject: [PATCH 32/41] Jacobians should not be computed only for transforms --- GPy/core/parameterization/parameter_core.py | 1 + 1 file changed, 1 insertion(+) diff --git a/GPy/core/parameterization/parameter_core.py b/GPy/core/parameterization/parameter_core.py index 067960ce..48c05a8d 100644 --- a/GPy/core/parameterization/parameter_core.py +++ b/GPy/core/parameterization/parameter_core.py @@ -457,6 +457,7 @@ class Indexable(Nameable, Updateable): #add in jacobian derivatives if transformed priored_indexes = np.hstack([i for p, i in self.priors.items()]) for c,j in self.constraints.items(): + if not isinstance(c, Transformation):continue for jj in j: if jj in priored_indexes: ret[jj] += c.log_jacobian_grad(x[jj]) From 04c14a9b4cf77414a4b30a9a391570dea79cc0e5 Mon Sep 17 00:00:00 2001 From: James Hensman Date: Mon, 8 Jun 2015 15:25:16 +0100 Subject: [PATCH 33/41] parallelizing backprop of cholesky --- GPy/util/choleskies_cython.c | 14309 ++++++++++++++++++++++++++++++- GPy/util/choleskies_cython.pyx | 28 + GPy/util/cholesky_backprop.c | 22 + GPy/util/cholesky_backprop.h | 1 + setup.py | 2 +- 5 files changed, 14239 insertions(+), 123 deletions(-) create mode 100644 GPy/util/cholesky_backprop.c create mode 100644 GPy/util/cholesky_backprop.h diff --git a/GPy/util/choleskies_cython.c b/GPy/util/choleskies_cython.c index 069fb478..c5d1867e 100644 --- a/GPy/util/choleskies_cython.c +++ b/GPy/util/choleskies_cython.c @@ -231,6 +231,9 @@ void __Pyx_call_destructor(T* x) { #include "stdlib.h" #include "numpy/arrayobject.h" #include "numpy/ufuncobject.h" +#include "cholesky_backprop.h" +#include "pythread.h" +#include "pystate.h" #ifdef _OPENMP #include #endif /* _OPENMP */ @@ -436,6 +439,7 @@ static const char *__pyx_filename; static const char *__pyx_f[] = { "GPy/util/choleskies_cython.pyx", "__init__.pxd", + "GPy/util/stringsource", "type.pxd", }; #define IS_UNSIGNED(type) (((type) -1) > 0) @@ -473,6 +477,62 @@ typedef struct { char is_valid_array; } __Pyx_BufFmt_Context; +struct __pyx_memoryview_obj; +typedef struct { + struct __pyx_memoryview_obj *memview; + char *data; + Py_ssize_t shape[8]; + Py_ssize_t strides[8]; + Py_ssize_t suboffsets[8]; +} __Pyx_memviewslice; + +#include +#ifndef CYTHON_ATOMICS + #define CYTHON_ATOMICS 1 +#endif +#define __pyx_atomic_int_type int +#if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 || \ + (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) && \ + !defined(__i386__) + #define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1) + #define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1) + #ifdef __PYX_DEBUG_ATOMICS + #warning "Using GNU atomics" + #endif +#elif CYTHON_ATOMICS && MSC_VER + #include + #define __pyx_atomic_int_type LONG + #define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value) + #define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value) + #ifdef __PYX_DEBUG_ATOMICS + #warning "Using MSVC atomics" + #endif +#elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0 + #define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value) + #define __pyx_atomic_decr_aligned(value, lock) _InterlockedDecrement(value) + #ifdef __PYX_DEBUG_ATOMICS + #warning "Using Intel atomics" + #endif +#else + #undef CYTHON_ATOMICS + #define CYTHON_ATOMICS 0 + #ifdef __PYX_DEBUG_ATOMICS + #warning "Not using atomics" + #endif +#endif +typedef volatile __pyx_atomic_int_type __pyx_atomic_int; +#if CYTHON_ATOMICS + #define __pyx_add_acquisition_count(memview) \ + __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) + #define __pyx_sub_acquisition_count(memview) \ + __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) +#else + #define __pyx_add_acquisition_count(memview) \ + __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) + #define __pyx_sub_acquisition_count(memview) \ + __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) +#endif + /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":723 * # in Cython to enable them only on the right systems. @@ -684,6 +744,10 @@ typedef npy_longdouble __pyx_t_5numpy_longdouble_t; /*--- Type declarations ---*/ +struct __pyx_array_obj; +struct __pyx_MemviewEnum_obj; +struct __pyx_memoryview_obj; +struct __pyx_memoryviewslice_obj; /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":762 * ctypedef npy_longdouble longdouble_t @@ -720,6 +784,116 @@ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; * cdef inline object PyArray_MultiIterNew1(a): */ typedef npy_cdouble __pyx_t_5numpy_complex_t; + +/* "View.MemoryView":99 + * + * @cname("__pyx_array") + * cdef class array: # <<<<<<<<<<<<<< + * + * cdef: + */ +struct __pyx_array_obj { + PyObject_HEAD + char *data; + Py_ssize_t len; + char *format; + int ndim; + Py_ssize_t *_shape; + Py_ssize_t *_strides; + Py_ssize_t itemsize; + PyObject *mode; + PyObject *_format; + void (*callback_free_data)(void *); + int free_data; + int dtype_is_object; +}; + + +/* "View.MemoryView":269 + * + * @cname('__pyx_MemviewEnum') + * cdef class Enum(object): # <<<<<<<<<<<<<< + * cdef object name + * def __init__(self, name): + */ +struct __pyx_MemviewEnum_obj { + PyObject_HEAD + PyObject *name; +}; + + +/* "View.MemoryView":302 + * + * @cname('__pyx_memoryview') + * cdef class memoryview(object): # <<<<<<<<<<<<<< + * + * cdef object obj + */ +struct __pyx_memoryview_obj { + PyObject_HEAD + struct __pyx_vtabstruct_memoryview *__pyx_vtab; + PyObject *obj; + PyObject *_size; + PyObject *_array_interface; + PyThread_type_lock lock; + __pyx_atomic_int acquisition_count[2]; + __pyx_atomic_int *acquisition_count_aligned_p; + Py_buffer view; + int flags; + int dtype_is_object; + __Pyx_TypeInfo *typeinfo; +}; + + +/* "View.MemoryView":922 + * + * @cname('__pyx_memoryviewslice') + * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< + * "Internal class for passing memoryview slices to Python" + * + */ +struct __pyx_memoryviewslice_obj { + struct __pyx_memoryview_obj __pyx_base; + __Pyx_memviewslice from_slice; + PyObject *from_object; + PyObject *(*to_object_func)(char *); + int (*to_dtype_func)(char *, PyObject *); +}; + + + +/* "View.MemoryView":302 + * + * @cname('__pyx_memoryview') + * cdef class memoryview(object): # <<<<<<<<<<<<<< + * + * cdef object obj + */ + +struct __pyx_vtabstruct_memoryview { + char *(*get_item_pointer)(struct __pyx_memoryview_obj *, PyObject *); + PyObject *(*is_slice)(struct __pyx_memoryview_obj *, PyObject *); + PyObject *(*setitem_slice_assignment)(struct __pyx_memoryview_obj *, PyObject *, PyObject *); + PyObject *(*setitem_slice_assign_scalar)(struct __pyx_memoryview_obj *, struct __pyx_memoryview_obj *, PyObject *); + PyObject *(*setitem_indexed)(struct __pyx_memoryview_obj *, PyObject *, PyObject *); + PyObject *(*convert_item_to_object)(struct __pyx_memoryview_obj *, char *); + PyObject *(*assign_item_from_object)(struct __pyx_memoryview_obj *, char *, PyObject *); +}; +static struct __pyx_vtabstruct_memoryview *__pyx_vtabptr_memoryview; + + +/* "View.MemoryView":922 + * + * @cname('__pyx_memoryviewslice') + * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< + * "Internal class for passing memoryview slices to Python" + * + */ + +struct __pyx_vtabstruct__memoryviewslice { + struct __pyx_vtabstruct_memoryview __pyx_base; +}; +static struct __pyx_vtabstruct__memoryviewslice *__pyx_vtabptr__memoryviewslice; #ifndef CYTHON_REFNANNY #define CYTHON_REFNANNY 0 #endif @@ -844,6 +1018,31 @@ static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func); #define __Pyx_PyObject_CallNoArg(func) __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL) #endif +#define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d +#define __Pyx_MEMVIEW_DIRECT 1 +#define __Pyx_MEMVIEW_PTR 2 +#define __Pyx_MEMVIEW_FULL 4 +#define __Pyx_MEMVIEW_CONTIG 8 +#define __Pyx_MEMVIEW_STRIDED 16 +#define __Pyx_MEMVIEW_FOLLOW 32 +#define __Pyx_IS_C_CONTIG 1 +#define __Pyx_IS_F_CONTIG 2 +static int __Pyx_init_memviewslice( + struct __pyx_memoryview_obj *memview, + int ndim, + __Pyx_memviewslice *memviewslice, + int memview_is_new_reference); +static CYTHON_INLINE int __pyx_add_acquisition_count_locked( + __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); +static CYTHON_INLINE int __pyx_sub_acquisition_count_locked( + __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); +#define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p) +#define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview)) +#define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__) +#define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__) +static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int); +static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int); + static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); @@ -852,6 +1051,126 @@ static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); +#include + +static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals); + +static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals); + +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyString_Equals __Pyx_PyUnicode_Equals +#else +#define __Pyx_PyString_Equals __Pyx_PyBytes_Equals +#endif + +static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t, Py_ssize_t); /* proto */ + +#ifndef __PYX_FORCE_INIT_THREADS + #define __PYX_FORCE_INIT_THREADS 0 +#endif + +#define UNARY_NEG_WOULD_OVERFLOW(x) (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x))) + +static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ +static PyObject *get_memview(PyObject *__pyx_v_self); /*proto*/ +static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *); + +static CYTHON_INLINE PyObject* __Pyx_decode_c_string( + const char* cstring, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)); + +static CYTHON_INLINE void __Pyx_ExceptionSave(PyObject **type, PyObject **value, PyObject **tb); +static void __Pyx_ExceptionReset(PyObject *type, PyObject *value, PyObject *tb); + +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); + +static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb); + +#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \ + __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) : \ + (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) : \ + __Pyx_GetItemInt_Generic(o, to_py_func(i)))) +#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \ + __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) : \ + (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \ + __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) : \ + (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j); +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, + int is_list, int wraparound, int boundscheck); + +static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ +static PyObject *__pyx_memoryview_transpose(PyObject *__pyx_v_self); /*proto*/ +static PyObject *__pyx_memoryview__get__base(PyObject *__pyx_v_self); /*proto*/ +static PyObject *__pyx_memoryview_get_shape(PyObject *__pyx_v_self); /*proto*/ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { + PyListObject* L = (PyListObject*) list; + Py_ssize_t len = Py_SIZE(list); + if (likely(L->allocated > len)) { + Py_INCREF(x); + PyList_SET_ITEM(list, len, x); + Py_SIZE(list) = len+1; + return 0; + } + return PyList_Append(list, x); +} +#else +#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x) +#endif + +static PyObject *__pyx_memoryview_get_strides(PyObject *__pyx_v_self); /*proto*/ +static PyObject *__pyx_memoryview_get_suboffsets(PyObject *__pyx_v_self); /*proto*/ +static PyObject *__pyx_memoryview_get_ndim(PyObject *__pyx_v_self); /*proto*/ +static PyObject *__pyx_memoryview_get_itemsize(PyObject *__pyx_v_self); /*proto*/ +static PyObject *__pyx_memoryview_get_nbytes(PyObject *__pyx_v_self); /*proto*/ +static PyObject *__pyx_memoryview_get_size(PyObject *__pyx_v_self); /*proto*/ +static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) { +#if CYTHON_COMPILING_IN_CPYTHON + PyObject* none = _PyList_Extend((PyListObject*)L, v); + if (unlikely(!none)) + return -1; + Py_DECREF(none); + return 0; +#else + return PyList_SetSlice(L, PY_SSIZE_T_MAX, PY_SSIZE_T_MAX, v); +#endif +} + +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { + PyListObject* L = (PyListObject*) list; + Py_ssize_t len = Py_SIZE(list); + if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) { + Py_INCREF(x); + PyList_SET_ITEM(list, len, x); + Py_SIZE(list) = len+1; + return 0; + } + return PyList_Append(list, x); +} +#else +#define __Pyx_PyList_Append(L,x) PyList_Append(L,x) +#endif + +static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname); + +static PyObject *__pyx_memoryviewslice__get__base(PyObject *__pyx_v_self); /*proto*/ +static void __Pyx_WriteUnraisable(const char *name, int clineno, + int lineno, const char *filename, + int full_traceback); + +static int __Pyx_SetVtable(PyObject *dict, void *vtable); + typedef struct { int code_line; PyCodeObject* code_object; @@ -898,10 +1217,27 @@ static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); +static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b); + +static int __Pyx_ValidateAndInit_memviewslice( + int *axes_specs, + int c_or_f_flag, + int buf_flags, + int ndim, + __Pyx_TypeInfo *dtype, + __Pyx_BufFmt_StackElem stack[], + __Pyx_memviewslice *memviewslice, + PyObject *original_obj); + +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_double(PyObject *); + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); +static PyObject *__pyx_memview_get_double(const char *itemp); +static int __pyx_memview_set_double(const char *itemp, PyObject *obj); + #if CYTHON_CCOMPLEX #ifdef __cplusplus #define __Pyx_CREAL(z) ((z).real()) @@ -1000,6 +1336,23 @@ static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(do #endif #endif +static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice *mvs, + char order, int ndim); + +static int __pyx_slices_overlap(__Pyx_memviewslice *slice1, + __Pyx_memviewslice *slice2, + int ndim, size_t itemsize); + +static __Pyx_memviewslice +__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, + const char *mode, int ndim, + size_t sizeof_dtype, int contig_flag, + int dtype_is_object); + +static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig); + +static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *); + static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); static int __Pyx_check_binary_version(void); @@ -1018,6 +1371,15 @@ static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); +static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ +static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/ +static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/ +static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ +static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ +static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ /* Module declarations from 'cpython.buffer' */ @@ -1047,6 +1409,47 @@ static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *, char *, char *, int *); /*proto*/ /* Module declarations from 'GPy.util.choleskies_cython' */ +static PyTypeObject *__pyx_array_type = 0; +static PyTypeObject *__pyx_MemviewEnum_type = 0; +static PyTypeObject *__pyx_memoryview_type = 0; +static PyTypeObject *__pyx_memoryviewslice_type = 0; +static PyObject *generic = 0; +static PyObject *strided = 0; +static PyObject *indirect = 0; +static PyObject *contiguous = 0; +static PyObject *indirect_contiguous = 0; +static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/ +static void *__pyx_align_pointer(void *, size_t); /*proto*/ +static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/ +static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/ +static PyObject *_unellipsify(PyObject *, int); /*proto*/ +static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/ +static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/ +static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/ +static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/ +static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/ +static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/ +static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/ +static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/ +static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/ +static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/ +static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/ +static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/ +static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/ +static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/ +static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/ +static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/ +static int __pyx_memoryview_err(PyObject *, char *); /*proto*/ +static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/ +static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/ +static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/ +static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ +static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ +static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/ +static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/ static __Pyx_TypeInfo __Pyx_TypeInfo_double = { "double", NULL, sizeof(double), { 0 }, 0, 'R', 0, 0 }; #define __Pyx_MODULE_NAME "GPy.util.choleskies_cython" int __pyx_module_is_main_GPy__util__choleskies_cython = 0; @@ -1055,11 +1458,56 @@ int __pyx_module_is_main_GPy__util__choleskies_cython = 0; static PyObject *__pyx_builtin_range; static PyObject *__pyx_builtin_ValueError; static PyObject *__pyx_builtin_RuntimeError; +static PyObject *__pyx_builtin_MemoryError; +static PyObject *__pyx_builtin_enumerate; +static PyObject *__pyx_builtin_Ellipsis; +static PyObject *__pyx_builtin_TypeError; +static PyObject *__pyx_builtin_xrange; +static PyObject *__pyx_builtin_id; +static PyObject *__pyx_builtin_IndexError; static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_flat, int __pyx_v_M); /* proto */ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_L); /* proto */ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_4backprop_gradient(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_dL, PyArrayObject *__pyx_v_L); /* proto */ +static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_dL, __Pyx_memviewslice __pyx_v_L); /* proto */ +static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_8backprop_gradient_par_c(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_dL, PyArrayObject *__pyx_v_L); /* proto */ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */ +static int __pyx_array_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ +static int __pyx_array_getbuffer_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static void __pyx_array_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *get_memview_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_array_MemoryView_5array_6__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */ +static PyObject *__pyx_array_MemoryView_5array_8__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */ +static int __pyx_array_MemoryView_5array_10__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */ +static int __pyx_MemviewEnum_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */ +static PyObject *__pyx_MemviewEnum_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ +static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */ +static void __pyx_memoryview_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */ +static int __pyx_memoryview_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */ +static int __pyx_memoryview_getbuffer_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static PyObject *__pyx_memoryview_transpose_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview__get__base_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_get_shape_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_get_strides_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_get_suboffsets_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_get_ndim_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_get_itemsize_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_get_nbytes_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_get_size_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static Py_ssize_t __pyx_memoryview_MemoryView_10memoryview_10__len__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_MemoryView_10memoryview_12__repr__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_MemoryView_10memoryview_14__str__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_MemoryView_10memoryview_16is_c_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_MemoryView_10memoryview_18is_f_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_MemoryView_10memoryview_20copy(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview_MemoryView_10memoryview_22copy_fortran(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static void __pyx_memoryviewslice_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryviewslice__get__base_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static char __pyx_k_B[] = "B"; static char __pyx_k_D[] = "D"; static char __pyx_k_H[] = "H"; @@ -1070,6 +1518,7 @@ static char __pyx_k_N[] = "N"; static char __pyx_k_O[] = "O"; static char __pyx_k_Q[] = "Q"; static char __pyx_k_b[] = "b"; +static char __pyx_k_c[] = "c"; static char __pyx_k_d[] = "d"; static char __pyx_k_f[] = "f"; static char __pyx_k_g[] = "g"; @@ -1084,72 +1533,193 @@ static char __pyx_k_Zd[] = "Zd"; static char __pyx_k_Zf[] = "Zf"; static char __pyx_k_Zg[] = "Zg"; static char __pyx_k_dL[] = "dL"; +static char __pyx_k_id[] = "id"; static char __pyx_k_mm[] = "mm"; static char __pyx_k_np[] = "np"; +static char __pyx_k_obj[] = "obj"; static char __pyx_k_ret[] = "ret"; +static char __pyx_k_base[] = "base"; static char __pyx_k_copy[] = "copy"; static char __pyx_k_flat[] = "flat"; static char __pyx_k_main[] = "__main__"; +static char __pyx_k_mode[] = "mode"; +static char __pyx_k_name[] = "name"; +static char __pyx_k_ndim[] = "ndim"; +static char __pyx_k_pack[] = "pack"; +static char __pyx_k_size[] = "size"; +static char __pyx_k_step[] = "step"; +static char __pyx_k_stop[] = "stop"; static char __pyx_k_test[] = "__test__"; static char __pyx_k_tril[] = "tril"; +static char __pyx_k_class[] = "__class__"; static char __pyx_k_count[] = "count"; static char __pyx_k_dL_dK[] = "dL_dK"; static char __pyx_k_empty[] = "empty"; +static char __pyx_k_error[] = "error"; +static char __pyx_k_flags[] = "flags"; static char __pyx_k_numpy[] = "numpy"; static char __pyx_k_range[] = "range"; +static char __pyx_k_shape[] = "shape"; +static char __pyx_k_start[] = "start"; static char __pyx_k_zeros[] = "zeros"; +static char __pyx_k_format[] = "format"; static char __pyx_k_import[] = "__import__"; +static char __pyx_k_name_2[] = "__name__"; +static char __pyx_k_struct[] = "struct"; +static char __pyx_k_unpack[] = "unpack"; +static char __pyx_k_xrange[] = "xrange"; +static char __pyx_k_fortran[] = "fortran"; +static char __pyx_k_memview[] = "memview"; +static char __pyx_k_Ellipsis[] = "Ellipsis"; +static char __pyx_k_itemsize[] = "itemsize"; +static char __pyx_k_TypeError[] = "TypeError"; +static char __pyx_k_enumerate[] = "enumerate"; +static char __pyx_k_IndexError[] = "IndexError"; static char __pyx_k_ValueError[] = "ValueError"; +static char __pyx_k_pyx_vtable[] = "__pyx_vtable__"; +static char __pyx_k_MemoryError[] = "MemoryError"; static char __pyx_k_RuntimeError[] = "RuntimeError"; +static char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer"; static char __pyx_k_flat_to_triang[] = "flat_to_triang"; static char __pyx_k_triang_to_flat[] = "triang_to_flat"; +static char __pyx_k_allocate_buffer[] = "allocate_buffer"; +static char __pyx_k_dtype_is_object[] = "dtype_is_object"; static char __pyx_k_backprop_gradient[] = "backprop_gradient"; +static char __pyx_k_strided_and_direct[] = ""; +static char __pyx_k_strided_and_indirect[] = ""; +static char __pyx_k_backprop_gradient_par[] = "backprop_gradient_par"; +static char __pyx_k_contiguous_and_direct[] = ""; +static char __pyx_k_MemoryView_of_r_object[] = ""; +static char __pyx_k_MemoryView_of_r_at_0x_x[] = ""; +static char __pyx_k_backprop_gradient_par_c[] = "backprop_gradient_par_c"; +static char __pyx_k_contiguous_and_indirect[] = ""; +static char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'"; +static char __pyx_k_getbuffer_obj_view_flags[] = "getbuffer(obj, view, flags)"; +static char __pyx_k_Dimension_d_is_not_direct[] = "Dimension %d is not direct"; +static char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d."; static char __pyx_k_GPy_util_choleskies_cython[] = "GPy.util.choleskies_cython"; +static char __pyx_k_Index_out_of_bounds_axis_d[] = "Index out of bounds (axis %d)"; +static char __pyx_k_Step_may_not_be_zero_axis_d[] = "Step may not be zero (axis %d)"; +static char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array"; static char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous"; +static char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; +static char __pyx_k_strided_and_direct_or_indirect[] = ""; static char __pyx_k_home_james_work_GPy_GPy_util_ch[] = "/home/james/work/GPy/GPy/util/choleskies_cython.pyx"; static char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)"; +static char __pyx_k_All_dimensions_preceding_dimensi[] = "All dimensions preceding dimension %d must be indexed and not sliced"; +static char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; +static char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory."; +static char __pyx_k_Cannot_transpose_memoryview_with[] = "Cannot transpose memoryview with indirect dimensions"; +static char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array"; static char __pyx_k_Format_string_allocated_too_shor[] = "Format string allocated too short, see comment in numpy.pxd"; +static char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported"; +static char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s"; static char __pyx_k_Non_native_byte_order_not_suppor[] = "Non-native byte order not supported"; +static char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)"; +static char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object"; +static char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)"; static char __pyx_k_ndarray_is_not_Fortran_contiguou[] = "ndarray is not Fortran contiguous"; +static char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides."; static char __pyx_k_Format_string_allocated_too_shor_2[] = "Format string allocated too short."; +static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri; +static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is; +static PyObject *__pyx_kp_s_Cannot_index_with_type_s; static PyObject *__pyx_n_s_D; +static PyObject *__pyx_n_s_Ellipsis; +static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr; static PyObject *__pyx_kp_u_Format_string_allocated_too_shor; static PyObject *__pyx_kp_u_Format_string_allocated_too_shor_2; static PyObject *__pyx_n_s_GPy_util_choleskies_cython; +static PyObject *__pyx_n_s_IndexError; +static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte; +static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr; +static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d; static PyObject *__pyx_n_s_L; static PyObject *__pyx_n_s_M; +static PyObject *__pyx_n_s_MemoryError; +static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x; +static PyObject *__pyx_kp_s_MemoryView_of_r_object; static PyObject *__pyx_n_s_N; static PyObject *__pyx_kp_u_Non_native_byte_order_not_suppor; +static PyObject *__pyx_n_b_O; +static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a; static PyObject *__pyx_n_s_RuntimeError; +static PyObject *__pyx_n_s_TypeError; +static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object; static PyObject *__pyx_n_s_ValueError; +static PyObject *__pyx_n_s_allocate_buffer; static PyObject *__pyx_n_s_backprop_gradient; +static PyObject *__pyx_n_s_backprop_gradient_par; +static PyObject *__pyx_n_s_backprop_gradient_par_c; +static PyObject *__pyx_n_s_base; +static PyObject *__pyx_n_s_c; +static PyObject *__pyx_n_u_c; +static PyObject *__pyx_n_s_class; +static PyObject *__pyx_kp_s_contiguous_and_direct; +static PyObject *__pyx_kp_s_contiguous_and_indirect; static PyObject *__pyx_n_s_copy; static PyObject *__pyx_n_s_count; static PyObject *__pyx_n_s_d; static PyObject *__pyx_n_s_dL; static PyObject *__pyx_n_s_dL_dK; +static PyObject *__pyx_n_s_dtype_is_object; static PyObject *__pyx_n_s_empty; +static PyObject *__pyx_n_s_enumerate; +static PyObject *__pyx_n_s_error; +static PyObject *__pyx_n_s_flags; static PyObject *__pyx_n_s_flat; static PyObject *__pyx_n_s_flat_to_triang; +static PyObject *__pyx_n_s_format; +static PyObject *__pyx_n_s_fortran; +static PyObject *__pyx_n_u_fortran; +static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi; static PyObject *__pyx_kp_s_home_james_work_GPy_GPy_util_ch; static PyObject *__pyx_n_s_i; +static PyObject *__pyx_n_s_id; static PyObject *__pyx_n_s_import; +static PyObject *__pyx_n_s_itemsize; +static PyObject *__pyx_kp_s_itemsize_0_for_cython_array; static PyObject *__pyx_n_s_j; static PyObject *__pyx_n_s_k; static PyObject *__pyx_n_s_m; static PyObject *__pyx_n_s_main; +static PyObject *__pyx_n_s_memview; static PyObject *__pyx_n_s_mm; +static PyObject *__pyx_n_s_mode; +static PyObject *__pyx_n_s_name; +static PyObject *__pyx_n_s_name_2; static PyObject *__pyx_kp_u_ndarray_is_not_C_contiguous; static PyObject *__pyx_kp_u_ndarray_is_not_Fortran_contiguou; +static PyObject *__pyx_n_s_ndim; static PyObject *__pyx_n_s_np; static PyObject *__pyx_n_s_numpy; +static PyObject *__pyx_n_s_obj; +static PyObject *__pyx_n_s_pack; +static PyObject *__pyx_n_s_pyx_getbuffer; +static PyObject *__pyx_n_s_pyx_vtable; static PyObject *__pyx_n_s_range; static PyObject *__pyx_n_s_ret; +static PyObject *__pyx_n_s_shape; +static PyObject *__pyx_n_s_size; +static PyObject *__pyx_n_s_start; +static PyObject *__pyx_n_s_step; +static PyObject *__pyx_n_s_stop; +static PyObject *__pyx_kp_s_strided_and_direct; +static PyObject *__pyx_kp_s_strided_and_direct_or_indirect; +static PyObject *__pyx_kp_s_strided_and_indirect; +static PyObject *__pyx_n_s_struct; static PyObject *__pyx_n_s_test; static PyObject *__pyx_n_s_triang_to_flat; static PyObject *__pyx_n_s_tril; +static PyObject *__pyx_kp_s_unable_to_allocate_array_data; +static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str; static PyObject *__pyx_kp_u_unknown_dtype_code_in_numpy_pxd; +static PyObject *__pyx_n_s_unpack; +static PyObject *__pyx_n_s_xrange; static PyObject *__pyx_n_s_zeros; +static PyObject *__pyx_int_0; +static PyObject *__pyx_int_1; +static PyObject *__pyx_int_neg_1; static PyObject *__pyx_tuple_; static PyObject *__pyx_tuple__2; static PyObject *__pyx_tuple__3; @@ -1157,13 +1727,33 @@ static PyObject *__pyx_tuple__4; static PyObject *__pyx_tuple__5; static PyObject *__pyx_tuple__6; static PyObject *__pyx_tuple__7; +static PyObject *__pyx_tuple__8; static PyObject *__pyx_tuple__9; +static PyObject *__pyx_slice__14; +static PyObject *__pyx_slice__15; +static PyObject *__pyx_slice__16; +static PyObject *__pyx_tuple__10; static PyObject *__pyx_tuple__11; -static PyObject *__pyx_codeobj__8; -static PyObject *__pyx_codeobj__10; -static PyObject *__pyx_codeobj__12; +static PyObject *__pyx_tuple__12; +static PyObject *__pyx_tuple__13; +static PyObject *__pyx_tuple__17; +static PyObject *__pyx_tuple__18; +static PyObject *__pyx_tuple__20; +static PyObject *__pyx_tuple__22; +static PyObject *__pyx_tuple__24; +static PyObject *__pyx_tuple__26; +static PyObject *__pyx_tuple__28; +static PyObject *__pyx_tuple__29; +static PyObject *__pyx_tuple__30; +static PyObject *__pyx_tuple__31; +static PyObject *__pyx_tuple__32; +static PyObject *__pyx_codeobj__19; +static PyObject *__pyx_codeobj__21; +static PyObject *__pyx_codeobj__23; +static PyObject *__pyx_codeobj__25; +static PyObject *__pyx_codeobj__27; -/* "GPy/util/choleskies_cython.pyx":10 +/* "GPy/util/choleskies_cython.pyx":11 * cimport numpy as np * * def flat_to_triang(np.ndarray[double, ndim=2] flat, int M): # <<<<<<<<<<<<<< @@ -1204,11 +1794,11 @@ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_1flat_to_triang(PyObjec case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_M)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("flat_to_triang", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 10; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("flat_to_triang", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 11; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "flat_to_triang") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 10; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "flat_to_triang") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 11; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else if (PyTuple_GET_SIZE(__pyx_args) != 2) { goto __pyx_L5_argtuple_error; @@ -1217,17 +1807,17 @@ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_1flat_to_triang(PyObjec values[1] = PyTuple_GET_ITEM(__pyx_args, 1); } __pyx_v_flat = ((PyArrayObject *)values[0]); - __pyx_v_M = __Pyx_PyInt_As_int(values[1]); if (unlikely((__pyx_v_M == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 10; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_M = __Pyx_PyInt_As_int(values[1]); if (unlikely((__pyx_v_M == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 11; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("flat_to_triang", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 10; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("flat_to_triang", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 11; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("GPy.util.choleskies_cython.flat_to_triang", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return NULL; __pyx_L4_argument_unpacking_done:; - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_flat), __pyx_ptype_5numpy_ndarray, 1, "flat", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 10; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_flat), __pyx_ptype_5numpy_ndarray, 1, "flat", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 11; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_r = __pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(__pyx_self, __pyx_v_flat, __pyx_v_M); /* function exit code */ @@ -1285,11 +1875,11 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U __pyx_pybuffernd_flat.rcbuffer = &__pyx_pybuffer_flat; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_flat.rcbuffer->pybuffer, (PyObject*)__pyx_v_flat, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 10; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_flat.rcbuffer->pybuffer, (PyObject*)__pyx_v_flat, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 11; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd_flat.diminfo[0].strides = __pyx_pybuffernd_flat.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_flat.diminfo[0].shape = __pyx_pybuffernd_flat.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd_flat.diminfo[1].strides = __pyx_pybuffernd_flat.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd_flat.diminfo[1].shape = __pyx_pybuffernd_flat.rcbuffer->pybuffer.shape[1]; - /* "GPy/util/choleskies_cython.pyx":17 + /* "GPy/util/choleskies_cython.pyx":18 * the lower triangluar portion of the d'th slice of the result is filled by the d'th column of flat. * """ * cdef int D = flat.shape[1] # <<<<<<<<<<<<<< @@ -1298,7 +1888,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U */ __pyx_v_D = (__pyx_v_flat->dimensions[1]); - /* "GPy/util/choleskies_cython.pyx":18 + /* "GPy/util/choleskies_cython.pyx":19 * """ * cdef int D = flat.shape[1] * cdef int N = flat.shape[0] # <<<<<<<<<<<<<< @@ -1307,7 +1897,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U */ __pyx_v_N = (__pyx_v_flat->dimensions[0]); - /* "GPy/util/choleskies_cython.pyx":19 + /* "GPy/util/choleskies_cython.pyx":20 * cdef int D = flat.shape[1] * cdef int N = flat.shape[0] * cdef int count = 0 # <<<<<<<<<<<<<< @@ -1316,25 +1906,25 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_flat_to_triang(CYTHON_U */ __pyx_v_count = 0; - /* "GPy/util/choleskies_cython.pyx":20 + /* "GPy/util/choleskies_cython.pyx":21 * cdef int N = flat.shape[0] * cdef int count = 0 * cdef np.ndarray[double, ndim=3] ret = np.zeros((D, M, M)) # <<<<<<<<<<<<<< * cdef int d, m, mm * for d in range(D): */ - __pyx_t_2 = __Pyx_GetModuleGlobalName(__pyx_n_s_np); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = __Pyx_GetModuleGlobalName(__pyx_n_s_np); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 21; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); - __pyx_t_3 = __Pyx_PyObject_GetAttrStr(__pyx_t_2, __pyx_n_s_zeros); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyObject_GetAttrStr(__pyx_t_2, __pyx_n_s_zeros); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 21; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - __pyx_t_2 = __Pyx_PyInt_From_int(__pyx_v_D); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = __Pyx_PyInt_From_int(__pyx_v_D); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 21; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); - __pyx_t_4 = __Pyx_PyInt_From_int(__pyx_v_M); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyInt_From_int(__pyx_v_M); if 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__pyx_lineno = 36; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); PyTuple_SET_ITEM(__pyx_t_2, 0, __pyx_t_4); __Pyx_GIVEREF(__pyx_t_4); __pyx_t_4 = NULL; PyTuple_SET_ITEM(__pyx_t_2, 0+1, __pyx_t_5); __Pyx_GIVEREF(__pyx_t_5); __pyx_t_5 = 0; - __pyx_t_1 = __Pyx_PyObject_Call(__pyx_t_3, __pyx_t_2, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 35; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_Call(__pyx_t_3, __pyx_t_2, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 36; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; } __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 35; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 36; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_6 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_flat.rcbuffer->pybuffer, (PyObject*)__pyx_t_6, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES| PyBUF_WRITABLE, 2, 0, __pyx_stack) == -1)) { __pyx_v_flat = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_flat.rcbuffer->pybuffer.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 35; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 36; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_pybuffernd_flat.diminfo[0].strides = __pyx_pybuffernd_flat.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_flat.diminfo[0].shape = __pyx_pybuffernd_flat.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd_flat.diminfo[1].strides = __pyx_pybuffernd_flat.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd_flat.diminfo[1].shape = __pyx_pybuffernd_flat.rcbuffer->pybuffer.shape[1]; } } @@ -1684,7 +2274,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ __pyx_v_flat = ((PyArrayObject *)__pyx_t_1); __pyx_t_1 = 0; - /* "GPy/util/choleskies_cython.pyx":37 + /* "GPy/util/choleskies_cython.pyx":38 * cdef np.ndarray[double, ndim=2] flat = np.empty((N, D)) * cdef int d, m, mm * for d in range(D): # <<<<<<<<<<<<<< @@ -1695,7 +2285,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ for (__pyx_t_8 = 0; __pyx_t_8 < __pyx_t_7; __pyx_t_8+=1) { __pyx_v_d = __pyx_t_8; - /* "GPy/util/choleskies_cython.pyx":38 + /* "GPy/util/choleskies_cython.pyx":39 * cdef int d, m, mm * for d in range(D): * count = 0 # <<<<<<<<<<<<<< @@ -1704,7 +2294,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ */ __pyx_v_count = 0; - /* "GPy/util/choleskies_cython.pyx":39 + /* "GPy/util/choleskies_cython.pyx":40 * for d in range(D): * count = 0 * for m in range(M): # <<<<<<<<<<<<<< @@ -1715,7 +2305,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ for (__pyx_t_10 = 0; __pyx_t_10 < __pyx_t_9; __pyx_t_10+=1) { __pyx_v_m = __pyx_t_10; - /* "GPy/util/choleskies_cython.pyx":40 + /* "GPy/util/choleskies_cython.pyx":41 * count = 0 * for m in range(M): * for mm in range(m+1): # <<<<<<<<<<<<<< @@ -1726,7 +2316,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ for (__pyx_t_12 = 0; __pyx_t_12 < __pyx_t_11; __pyx_t_12+=1) { __pyx_v_mm = __pyx_t_12; - /* "GPy/util/choleskies_cython.pyx":41 + /* "GPy/util/choleskies_cython.pyx":42 * for m in range(M): * for mm in range(m+1): * flat[count,d] = L[d, m, mm] # <<<<<<<<<<<<<< @@ -1745,7 +2335,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ if (__pyx_t_17 < 0) __pyx_t_17 += __pyx_pybuffernd_flat.diminfo[1].shape; *__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_flat.rcbuffer->pybuffer.buf, __pyx_t_16, __pyx_pybuffernd_flat.diminfo[0].strides, __pyx_t_17, __pyx_pybuffernd_flat.diminfo[1].strides) = (*__Pyx_BufPtrStrided3d(double *, __pyx_pybuffernd_L.rcbuffer->pybuffer.buf, __pyx_t_13, __pyx_pybuffernd_L.diminfo[0].strides, __pyx_t_14, __pyx_pybuffernd_L.diminfo[1].strides, __pyx_t_15, __pyx_pybuffernd_L.diminfo[2].strides)); - /* "GPy/util/choleskies_cython.pyx":42 + /* "GPy/util/choleskies_cython.pyx":43 * for mm in range(m+1): * flat[count,d] = L[d, m, mm] * count += 1 # <<<<<<<<<<<<<< @@ -1757,7 +2347,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ } } - /* "GPy/util/choleskies_cython.pyx":43 + /* "GPy/util/choleskies_cython.pyx":44 * flat[count,d] = L[d, m, mm] * count += 1 * return flat # <<<<<<<<<<<<<< @@ -1769,7 +2359,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ __pyx_r = ((PyObject *)__pyx_v_flat); goto __pyx_L0; - /* "GPy/util/choleskies_cython.pyx":30 + /* "GPy/util/choleskies_cython.pyx":31 * return ret * * def triang_to_flat(np.ndarray[double, ndim=3] L): # <<<<<<<<<<<<<< @@ -1802,7 +2392,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ return __pyx_r; } -/* "GPy/util/choleskies_cython.pyx":46 +/* "GPy/util/choleskies_cython.pyx":47 * * * def backprop_gradient(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] L): # <<<<<<<<<<<<<< @@ -1842,11 +2432,11 @@ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_5backprop_gradient(PyOb case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_L)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("backprop_gradient", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("backprop_gradient", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "backprop_gradient") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "backprop_gradient") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else if (PyTuple_GET_SIZE(__pyx_args) != 2) { goto __pyx_L5_argtuple_error; @@ -1859,14 +2449,14 @@ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_5backprop_gradient(PyOb } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("backprop_gradient", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("backprop_gradient", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("GPy.util.choleskies_cython.backprop_gradient", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return NULL; __pyx_L4_argument_unpacking_done:; - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_dL), __pyx_ptype_5numpy_ndarray, 1, "dL", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_L), __pyx_ptype_5numpy_ndarray, 1, "L", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_dL), __pyx_ptype_5numpy_ndarray, 1, "dL", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_L), __pyx_ptype_5numpy_ndarray, 1, "L", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_r = __pyx_pf_3GPy_4util_17choleskies_cython_4backprop_gradient(__pyx_self, __pyx_v_dL, __pyx_v_L); /* function exit code */ @@ -1943,25 +2533,25 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_4backprop_gradient(CYTH __pyx_pybuffernd_L.rcbuffer = &__pyx_pybuffer_L; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_dL.rcbuffer->pybuffer, (PyObject*)__pyx_v_dL, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_dL.rcbuffer->pybuffer, (PyObject*)__pyx_v_dL, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd_dL.diminfo[0].strides = __pyx_pybuffernd_dL.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_dL.diminfo[0].shape = __pyx_pybuffernd_dL.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd_dL.diminfo[1].strides = __pyx_pybuffernd_dL.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd_dL.diminfo[1].shape = __pyx_pybuffernd_dL.rcbuffer->pybuffer.shape[1]; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_L.rcbuffer->pybuffer, (PyObject*)__pyx_v_L, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_L.rcbuffer->pybuffer, (PyObject*)__pyx_v_L, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd_L.diminfo[0].strides = __pyx_pybuffernd_L.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_L.diminfo[0].shape = __pyx_pybuffernd_L.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd_L.diminfo[1].strides = __pyx_pybuffernd_L.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd_L.diminfo[1].shape = __pyx_pybuffernd_L.rcbuffer->pybuffer.shape[1]; - /* "GPy/util/choleskies_cython.pyx":47 + /* "GPy/util/choleskies_cython.pyx":48 * * def backprop_gradient(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] L): * cdef np.ndarray[double, ndim=2] dL_dK = np.tril(dL).copy() # <<<<<<<<<<<<<< * cdef int N = L.shape[0] * cdef int k, j, i */ - __pyx_t_3 = __Pyx_GetModuleGlobalName(__pyx_n_s_np); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_GetModuleGlobalName(__pyx_n_s_np); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 48; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_4 = __Pyx_PyObject_GetAttrStr(__pyx_t_3, __pyx_n_s_tril); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyObject_GetAttrStr(__pyx_t_3, __pyx_n_s_tril); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 48; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __pyx_t_3 = NULL; @@ -1975,21 +2565,21 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_4backprop_gradient(CYTH } } if (!__pyx_t_3) { - __pyx_t_2 = __Pyx_PyObject_CallOneArg(__pyx_t_4, ((PyObject *)__pyx_v_dL)); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = __Pyx_PyObject_CallOneArg(__pyx_t_4, ((PyObject *)__pyx_v_dL)); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 48; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); } else { - __pyx_t_5 = PyTuple_New(1+1); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PyTuple_New(1+1); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 48; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); PyTuple_SET_ITEM(__pyx_t_5, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); __pyx_t_3 = NULL; __Pyx_INCREF(((PyObject *)__pyx_v_dL)); PyTuple_SET_ITEM(__pyx_t_5, 0+1, ((PyObject *)__pyx_v_dL)); __Pyx_GIVEREF(((PyObject *)__pyx_v_dL)); - __pyx_t_2 = __Pyx_PyObject_Call(__pyx_t_4, __pyx_t_5, NULL); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = __Pyx_PyObject_Call(__pyx_t_4, __pyx_t_5, NULL); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 48; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; } __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - __pyx_t_4 = __Pyx_PyObject_GetAttrStr(__pyx_t_2, __pyx_n_s_copy); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyObject_GetAttrStr(__pyx_t_2, __pyx_n_s_copy); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 48; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __pyx_t_2 = NULL; @@ -2003,20 +2593,20 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_4backprop_gradient(CYTH } } if (__pyx_t_2) { - __pyx_t_1 = __Pyx_PyObject_CallOneArg(__pyx_t_4, __pyx_t_2); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_CallOneArg(__pyx_t_4, __pyx_t_2); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 48; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; } else { - __pyx_t_1 = __Pyx_PyObject_CallNoArg(__pyx_t_4); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_CallNoArg(__pyx_t_4); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 48; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, 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for j in range(k + 1, N): * for i in range(j, N): * dL_dK[i, k] -= dL_dK[i, j] * L[j, k] # <<<<<<<<<<<<<< @@ -2086,7 +2676,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_4backprop_gradient(CYTH if (__pyx_t_17 < 0) __pyx_t_17 += __pyx_pybuffernd_dL_dK.diminfo[1].shape; *__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_dL_dK.rcbuffer->pybuffer.buf, __pyx_t_16, __pyx_pybuffernd_dL_dK.diminfo[0].strides, __pyx_t_17, __pyx_pybuffernd_dL_dK.diminfo[1].strides) -= ((*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_dL_dK.rcbuffer->pybuffer.buf, __pyx_t_12, __pyx_pybuffernd_dL_dK.diminfo[0].strides, __pyx_t_13, __pyx_pybuffernd_dL_dK.diminfo[1].strides)) * (*__Pyx_BufPtrStrided2d(double *, __pyx_pybuffernd_L.rcbuffer->pybuffer.buf, __pyx_t_14, __pyx_pybuffernd_L.diminfo[0].strides, __pyx_t_15, __pyx_pybuffernd_L.diminfo[1].strides))); - /* "GPy/util/choleskies_cython.pyx":54 + /* "GPy/util/choleskies_cython.pyx":55 * for i in range(j, N): * dL_dK[i, k] -= dL_dK[i, j] * L[j, k] * 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(__pyx_v_L.data + __pyx_t_17 * __pyx_v_L.strides[0]) ) + __pyx_t_18 * __pyx_v_L.strides[1]) )))); + } + + /* "GPy/util/choleskies_cython.pyx":71 + * for j in range(k+1, i+1): + * dL_dK[i, k] -= dL_dK[i, j] * L[j, k] + * for j in range(i, N): # <<<<<<<<<<<<<< + * dL_dK[i, k] -= dL_dK[j, i] * L[j, k] + * for j in range(k + 1, N): + */ + __pyx_t_14 = __pyx_v_N; + for (__pyx_t_21 = __pyx_v_i; __pyx_t_21 < __pyx_t_14; __pyx_t_21+=1) { + __pyx_v_j = __pyx_t_21; + + /* "GPy/util/choleskies_cython.pyx":72 + * dL_dK[i, k] -= dL_dK[i, j] * L[j, k] + * for j in range(i, N): + * dL_dK[i, k] -= dL_dK[j, i] * L[j, k] # <<<<<<<<<<<<<< + * for j in range(k + 1, N): + * dL_dK[j, k] /= L[k, k] + */ + __pyx_t_22 = __pyx_v_j; + __pyx_t_23 = __pyx_v_i; + if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_dL_dK.shape[0]; + if (__pyx_t_23 < 0) __pyx_t_23 += __pyx_v_dL_dK.shape[1]; + __pyx_t_24 = __pyx_v_j; + __pyx_t_25 = __pyx_v_k; + if (__pyx_t_24 < 0) __pyx_t_24 += __pyx_v_L.shape[0]; + if (__pyx_t_25 < 0) 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Py_None); + __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; + __pyx_v_have_stop = __pyx_t_1; + + /* "View.MemoryView":723 + * have_start = index.start is not None + * have_stop = index.stop is not None + * have_step = index.step is not None # <<<<<<<<<<<<<< + * + * slice_memviewslice( + */ + __pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_index, __pyx_n_s_step); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 723; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_9); + __pyx_t_1 = (__pyx_t_9 != Py_None); + __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; + __pyx_v_have_step = __pyx_t_1; + + /* "View.MemoryView":725 + * have_step = index.step is not None + * + * slice_memviewslice( # <<<<<<<<<<<<<< + * p_dst, p_src.shape[dim], p_src.strides[dim], p_src.suboffsets[dim], + * dim, new_ndim, p_suboffset_dim, + */ + __pyx_t_11 = __pyx_memoryview_slice_memviewslice(__pyx_v_p_dst, (__pyx_v_p_src->shape[__pyx_v_dim]), (__pyx_v_p_src->strides[__pyx_v_dim]), (__pyx_v_p_src->suboffsets[__pyx_v_dim]), __pyx_v_dim, __pyx_v_new_ndim, __pyx_v_p_suboffset_dim, __pyx_v_start, __pyx_v_stop, __pyx_v_step, __pyx_v_have_start, __pyx_v_have_stop, __pyx_v_have_step, 1); if (unlikely(__pyx_t_11 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 725; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "View.MemoryView":731 + * have_start, have_stop, have_step, + * True) + * new_ndim += 1 # <<<<<<<<<<<<<< + * + * if isinstance(memview, _memoryviewslice): + */ + __pyx_v_new_ndim = (__pyx_v_new_ndim + 1); + } + __pyx_L6:; + + /* "View.MemoryView":703 + * cdef bint have_start, have_stop, have_step + * + * for dim, index in enumerate(indices): # <<<<<<<<<<<<<< + * if PyIndex_Check(index): + * slice_memviewslice( + */ + } + __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; + + /* "View.MemoryView":733 + * new_ndim += 1 + * + * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< + * return memoryview_fromslice(dst, new_ndim, + * memviewsliceobj.to_object_func, + */ + __pyx_t_1 = __Pyx_TypeCheck(((PyObject *)__pyx_v_memview), ((PyObject *)__pyx_memoryviewslice_type)); + __pyx_t_2 = (__pyx_t_1 != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":734 + * + * if isinstance(memview, _memoryviewslice): + * return memoryview_fromslice(dst, new_ndim, # <<<<<<<<<<<<<< + * memviewsliceobj.to_object_func, + * memviewsliceobj.to_dtype_func, + */ + __Pyx_XDECREF(((PyObject *)__pyx_r)); + + /* "View.MemoryView":735 + * if isinstance(memview, _memoryviewslice): + * return memoryview_fromslice(dst, new_ndim, + * memviewsliceobj.to_object_func, # <<<<<<<<<<<<<< + * memviewsliceobj.to_dtype_func, + * memview.dtype_is_object) + */ + if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 735; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } + + /* "View.MemoryView":736 + * return memoryview_fromslice(dst, new_ndim, + * memviewsliceobj.to_object_func, + * memviewsliceobj.to_dtype_func, # <<<<<<<<<<<<<< + * memview.dtype_is_object) + * else: + */ + if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 736; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } + + /* "View.MemoryView":734 + * + * if isinstance(memview, _memoryviewslice): + * return memoryview_fromslice(dst, new_ndim, # <<<<<<<<<<<<<< + * memviewsliceobj.to_object_func, + * memviewsliceobj.to_dtype_func, + */ + __pyx_t_3 = __pyx_memoryview_fromslice(__pyx_v_dst, __pyx_v_new_ndim, __pyx_v_memviewsliceobj->to_object_func, __pyx_v_memviewsliceobj->to_dtype_func, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 734; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_3); + if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 734; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_r = ((struct __pyx_memoryview_obj *)__pyx_t_3); + __pyx_t_3 = 0; + goto __pyx_L0; + } + /*else*/ { + + /* "View.MemoryView":739 + * memview.dtype_is_object) + * else: + * return memoryview_fromslice(dst, new_ndim, NULL, NULL, # <<<<<<<<<<<<<< + * memview.dtype_is_object) + * + */ + __Pyx_XDECREF(((PyObject *)__pyx_r)); + + /* "View.MemoryView":740 + * else: + * return memoryview_fromslice(dst, new_ndim, NULL, NULL, + * memview.dtype_is_object) # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_3 = __pyx_memoryview_fromslice(__pyx_v_dst, __pyx_v_new_ndim, NULL, NULL, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 739; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_3); + + /* "View.MemoryView":739 + * memview.dtype_is_object) + * else: + * return memoryview_fromslice(dst, new_ndim, NULL, NULL, # <<<<<<<<<<<<<< + * memview.dtype_is_object) + * + */ + if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 739; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_r = ((struct __pyx_memoryview_obj *)__pyx_t_3); + __pyx_t_3 = 0; + goto __pyx_L0; + } + + /* "View.MemoryView":667 + * + * @cname('__pyx_memview_slice') + * cdef memoryview memview_slice(memoryview memview, object indices): # <<<<<<<<<<<<<< + * cdef int new_ndim = 0, suboffset_dim = -1, dim + * cdef bint negative_step + */ + + /* function exit code */ + __pyx_L1_error:; + __Pyx_XDECREF(__pyx_t_3); + __Pyx_XDECREF(__pyx_t_9); + __Pyx_AddTraceback("View.MemoryView.memview_slice", __pyx_clineno, __pyx_lineno, __pyx_filename); + __pyx_r = 0; + __pyx_L0:; + __Pyx_XDECREF((PyObject *)__pyx_v_memviewsliceobj); + __Pyx_XDECREF(__pyx_v_index); + __Pyx_XGIVEREF((PyObject *)__pyx_r); + __Pyx_RefNannyFinishContext(); + return __pyx_r; +} + +/* "View.MemoryView":764 + * + * @cname('__pyx_memoryview_slice_memviewslice') + * cdef int slice_memviewslice( # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * Py_ssize_t shape, Py_ssize_t stride, Py_ssize_t suboffset, + */ + +static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, Py_ssize_t __pyx_v_shape, Py_ssize_t __pyx_v_stride, Py_ssize_t __pyx_v_suboffset, int __pyx_v_dim, int __pyx_v_new_ndim, int *__pyx_v_suboffset_dim, Py_ssize_t __pyx_v_start, Py_ssize_t __pyx_v_stop, Py_ssize_t __pyx_v_step, int __pyx_v_have_start, int __pyx_v_have_stop, int __pyx_v_have_step, int __pyx_v_is_slice) { + Py_ssize_t __pyx_v_new_shape; + int __pyx_v_negative_step; + int __pyx_r; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; + + /* "View.MemoryView":784 + * cdef bint negative_step + * + * if not is_slice: # <<<<<<<<<<<<<< + * + * if start < 0: + */ + __pyx_t_1 = ((!(__pyx_v_is_slice != 0)) != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":786 + * if not is_slice: + * + * if start < 0: # <<<<<<<<<<<<<< + * start += shape + * if not 0 <= start < shape: + */ + __pyx_t_1 = ((__pyx_v_start < 0) != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":787 + * + * if start < 0: + * start += shape # <<<<<<<<<<<<<< + * if not 0 <= start < shape: + * _err_dim(IndexError, "Index out of bounds (axis %d)", dim) + */ + __pyx_v_start = (__pyx_v_start + __pyx_v_shape); + goto __pyx_L4; + } + __pyx_L4:; + + /* "View.MemoryView":788 + * if start < 0: + * start += shape + * if not 0 <= start < shape: # <<<<<<<<<<<<<< + * _err_dim(IndexError, "Index out of bounds (axis %d)", dim) + * else: + */ + __pyx_t_1 = (0 <= __pyx_v_start); + if (__pyx_t_1) { + __pyx_t_1 = (__pyx_v_start < __pyx_v_shape); + } + __pyx_t_2 = ((!(__pyx_t_1 != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":789 + * start += shape + * if not 0 <= start < shape: + * _err_dim(IndexError, "Index out of bounds (axis %d)", dim) # <<<<<<<<<<<<<< + * else: + * + */ + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, __pyx_k_Index_out_of_bounds_axis_d, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 789; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + goto __pyx_L5; + } + __pyx_L5:; + goto __pyx_L3; + } + /*else*/ { + + /* "View.MemoryView":792 + * else: + * + * negative_step = have_step != 0 and step < 0 # <<<<<<<<<<<<<< + * + * if have_step and step == 0: + */ + __pyx_t_1 = ((__pyx_v_have_step != 0) != 0); + if (__pyx_t_1) { + goto __pyx_L7_next_and; + } else { + __pyx_t_2 = __pyx_t_1; + goto __pyx_L6_bool_binop_done; + } + __pyx_L7_next_and:; + __pyx_t_1 = ((__pyx_v_step < 0) != 0); + __pyx_t_2 = __pyx_t_1; + __pyx_L6_bool_binop_done:; + __pyx_v_negative_step = __pyx_t_2; + + /* "View.MemoryView":794 + * negative_step = have_step != 0 and step < 0 + * + * if have_step and step == 0: # <<<<<<<<<<<<<< + * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) + * + */ + __pyx_t_1 = (__pyx_v_have_step != 0); + if (__pyx_t_1) { + goto __pyx_L10_next_and; + } else { + __pyx_t_2 = __pyx_t_1; + goto __pyx_L9_bool_binop_done; + } + __pyx_L10_next_and:; + __pyx_t_1 = ((__pyx_v_step == 0) != 0); + __pyx_t_2 = __pyx_t_1; + __pyx_L9_bool_binop_done:; + if (__pyx_t_2) { + + /* "View.MemoryView":795 + * + * if have_step and step == 0: + * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, __pyx_k_Step_may_not_be_zero_axis_d, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + goto __pyx_L8; + } + __pyx_L8:; + + /* "View.MemoryView":798 + * + * + * if have_start: # <<<<<<<<<<<<<< + * if start < 0: + * start += shape + */ + __pyx_t_2 = (__pyx_v_have_start != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":799 + * + * if have_start: + * if start < 0: # <<<<<<<<<<<<<< + * start += shape + * if start < 0: + */ + __pyx_t_2 = ((__pyx_v_start < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":800 + * if have_start: + * if start < 0: + * start += shape # <<<<<<<<<<<<<< + * if start < 0: + * start = 0 + */ + __pyx_v_start = (__pyx_v_start + __pyx_v_shape); + + /* "View.MemoryView":801 + * if start < 0: + * start += shape + * if start < 0: # <<<<<<<<<<<<<< + * start = 0 + * elif start >= shape: + */ + __pyx_t_2 = ((__pyx_v_start < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":802 + * start += shape + * if start < 0: + * start = 0 # <<<<<<<<<<<<<< + * elif start >= shape: + * if negative_step: + */ + __pyx_v_start = 0; + goto __pyx_L13; + } + __pyx_L13:; + goto __pyx_L12; + } + + /* "View.MemoryView":803 + * if start < 0: + * start = 0 + * elif start >= shape: # <<<<<<<<<<<<<< + * if negative_step: + * start = shape - 1 + */ + __pyx_t_2 = ((__pyx_v_start >= __pyx_v_shape) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":804 + * start = 0 + * elif start >= shape: + * if negative_step: # <<<<<<<<<<<<<< + * start = shape - 1 + * else: + */ + __pyx_t_2 = (__pyx_v_negative_step != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":805 + * elif start >= shape: + * if negative_step: + * start = shape - 1 # <<<<<<<<<<<<<< + * else: + * start = shape + */ + __pyx_v_start = (__pyx_v_shape - 1); + goto __pyx_L14; + } + /*else*/ { + + /* "View.MemoryView":807 + * start = shape - 1 + * else: + * start = shape # <<<<<<<<<<<<<< + * else: + * if negative_step: + */ + __pyx_v_start = __pyx_v_shape; + } + __pyx_L14:; + goto __pyx_L12; + } + __pyx_L12:; + goto __pyx_L11; + } + /*else*/ { + + /* "View.MemoryView":809 + * start = shape + * else: + * if negative_step: # <<<<<<<<<<<<<< + * start = shape - 1 + * else: + */ + __pyx_t_2 = (__pyx_v_negative_step != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":810 + * else: + * if negative_step: + * start = shape - 1 # <<<<<<<<<<<<<< + * else: + * start = 0 + */ + __pyx_v_start = (__pyx_v_shape - 1); + goto __pyx_L15; + } + /*else*/ { + + /* "View.MemoryView":812 + * start = shape - 1 + * else: + * start = 0 # <<<<<<<<<<<<<< + * + * if have_stop: + */ + __pyx_v_start = 0; + } + __pyx_L15:; + } + __pyx_L11:; + + /* "View.MemoryView":814 + * start = 0 + * + * if have_stop: # <<<<<<<<<<<<<< + * if stop < 0: + * stop += shape + */ + __pyx_t_2 = (__pyx_v_have_stop != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":815 + * + * if have_stop: + * if stop < 0: # <<<<<<<<<<<<<< + * stop += shape + * if stop < 0: + */ + __pyx_t_2 = ((__pyx_v_stop < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":816 + * if have_stop: + * if stop < 0: + * stop += shape # <<<<<<<<<<<<<< + * if stop < 0: + * stop = 0 + */ + __pyx_v_stop = (__pyx_v_stop + __pyx_v_shape); + + /* "View.MemoryView":817 + * if stop < 0: + * stop += shape + * if stop < 0: # <<<<<<<<<<<<<< + * stop = 0 + * elif stop > shape: + */ + __pyx_t_2 = ((__pyx_v_stop < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":818 + * stop += shape + * if stop < 0: + * stop = 0 # <<<<<<<<<<<<<< + * elif stop > shape: + * stop = shape + */ + __pyx_v_stop = 0; + goto __pyx_L18; + } + __pyx_L18:; + goto __pyx_L17; + } + + /* "View.MemoryView":819 + * if stop < 0: + * stop = 0 + * elif stop > shape: # <<<<<<<<<<<<<< + * stop = shape + * else: + */ + __pyx_t_2 = ((__pyx_v_stop > __pyx_v_shape) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":820 + * stop = 0 + * elif stop > shape: + * stop = shape # <<<<<<<<<<<<<< + * else: + * if negative_step: + */ + __pyx_v_stop = __pyx_v_shape; + goto __pyx_L17; + } + __pyx_L17:; + goto __pyx_L16; + } + /*else*/ { + + /* "View.MemoryView":822 + * stop = shape + * else: + * if negative_step: # <<<<<<<<<<<<<< + * stop = -1 + * else: + */ + __pyx_t_2 = (__pyx_v_negative_step != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":823 + * else: + * if negative_step: + * stop = -1 # <<<<<<<<<<<<<< + * else: + * stop = shape + */ + __pyx_v_stop = -1; + goto __pyx_L19; + } + /*else*/ { + + /* "View.MemoryView":825 + * stop = -1 + * else: + * stop = shape # <<<<<<<<<<<<<< + * + * if not have_step: + */ + __pyx_v_stop = __pyx_v_shape; + } + __pyx_L19:; + } + __pyx_L16:; + + /* "View.MemoryView":827 + * stop = shape + * + * if not have_step: # <<<<<<<<<<<<<< + * step = 1 + * + */ + __pyx_t_2 = ((!(__pyx_v_have_step != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":828 + * + * if not have_step: + * step = 1 # <<<<<<<<<<<<<< + * + * + */ + __pyx_v_step = 1; + goto __pyx_L20; + } + __pyx_L20:; + + /* "View.MemoryView":832 + * + * with cython.cdivision(True): + * new_shape = (stop - start) // step # <<<<<<<<<<<<<< + * + * if (stop - start) - step * new_shape: + */ + __pyx_v_new_shape = ((__pyx_v_stop - __pyx_v_start) / __pyx_v_step); + + /* "View.MemoryView":834 + * new_shape = (stop - start) // step + * + * if (stop - start) - step * new_shape: # <<<<<<<<<<<<<< + * new_shape += 1 + * + */ + __pyx_t_2 = (((__pyx_v_stop - __pyx_v_start) - (__pyx_v_step * __pyx_v_new_shape)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":835 + * + * if (stop - start) - step * new_shape: + * new_shape += 1 # <<<<<<<<<<<<<< + * + * if new_shape < 0: + */ + __pyx_v_new_shape = (__pyx_v_new_shape + 1); + goto __pyx_L21; + } + __pyx_L21:; + + /* "View.MemoryView":837 + * new_shape += 1 + * + * if new_shape < 0: # <<<<<<<<<<<<<< + * new_shape = 0 + * + */ + __pyx_t_2 = ((__pyx_v_new_shape < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":838 + * + * if new_shape < 0: + * new_shape = 0 # <<<<<<<<<<<<<< + * + * + */ + __pyx_v_new_shape = 0; + goto __pyx_L22; + } + __pyx_L22:; + + /* "View.MemoryView":841 + * + * + * dst.strides[new_ndim] = stride * step # <<<<<<<<<<<<<< + * dst.shape[new_ndim] = new_shape + * dst.suboffsets[new_ndim] = suboffset + */ + (__pyx_v_dst->strides[__pyx_v_new_ndim]) = (__pyx_v_stride * __pyx_v_step); + + /* "View.MemoryView":842 + * + * dst.strides[new_ndim] = stride * step + * dst.shape[new_ndim] = new_shape # <<<<<<<<<<<<<< + * 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cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<< + * if arg < 0: + * return -arg + */ + +static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { + Py_ssize_t __pyx_r; + int __pyx_t_1; + + /* "View.MemoryView":1063 + * + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: + * if arg < 0: # <<<<<<<<<<<<<< + * return -arg + * else: + */ + __pyx_t_1 = ((__pyx_v_arg < 0) != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1064 + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: + * if arg < 0: + * return -arg # <<<<<<<<<<<<<< + * else: + * return arg + */ + __pyx_r = (-__pyx_v_arg); + goto __pyx_L0; + } + /*else*/ { + + /* "View.MemoryView":1066 + * return -arg + * else: + * return arg # <<<<<<<<<<<<<< + * + * @cname('__pyx_get_best_slice_order') + */ + __pyx_r = __pyx_v_arg; + goto __pyx_L0; + } + + /* "View.MemoryView":1062 + * + * + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<< + * if arg < 0: + * return -arg + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1069 + * + * @cname('__pyx_get_best_slice_order') + * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< + * """ + * Figure out the best memory access order for a given slice. + */ + +static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim) { + int __pyx_v_i; + Py_ssize_t __pyx_v_c_stride; + Py_ssize_t __pyx_v_f_stride; + char __pyx_r; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + + /* "View.MemoryView":1074 + * """ + * cdef int i + * cdef Py_ssize_t c_stride = 0 # <<<<<<<<<<<<<< + * cdef Py_ssize_t f_stride = 0 + * + */ + __pyx_v_c_stride = 0; + + /* "View.MemoryView":1075 + * cdef int i + * cdef Py_ssize_t c_stride = 0 + * cdef Py_ssize_t f_stride = 0 # <<<<<<<<<<<<<< + * + * for i in range(ndim - 1, -1, -1): + */ + __pyx_v_f_stride = 0; + + /* "View.MemoryView":1077 + * cdef Py_ssize_t f_stride = 0 + * + * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< + * if mslice.shape[i] > 1: + * c_stride = mslice.strides[i] + */ + for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) { + __pyx_v_i = __pyx_t_1; + + /* "View.MemoryView":1078 + * + * for i in range(ndim - 1, -1, -1): + * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< + * c_stride = mslice.strides[i] + * break + */ + __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1079 + * for i in range(ndim - 1, -1, -1): + * if mslice.shape[i] > 1: + * c_stride = mslice.strides[i] # <<<<<<<<<<<<<< + * break + * + */ + __pyx_v_c_stride = (__pyx_v_mslice->strides[__pyx_v_i]); + + /* "View.MemoryView":1080 + * if mslice.shape[i] > 1: + * c_stride = mslice.strides[i] + * break # <<<<<<<<<<<<<< + * + * for i in range(ndim): + */ + goto __pyx_L4_break; + } + } + __pyx_L4_break:; + + /* "View.MemoryView":1082 + * break + * + * for i in range(ndim): # <<<<<<<<<<<<<< + * if mslice.shape[i] > 1: + * f_stride = mslice.strides[i] + */ + __pyx_t_1 = __pyx_v_ndim; + for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_1; __pyx_t_3+=1) { + __pyx_v_i = __pyx_t_3; + + /* "View.MemoryView":1083 + * + * for i in range(ndim): + * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< + * f_stride = mslice.strides[i] + * break + */ + __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1084 + * for i in range(ndim): + * if mslice.shape[i] > 1: + * f_stride = mslice.strides[i] # <<<<<<<<<<<<<< + * break + * + */ + __pyx_v_f_stride = (__pyx_v_mslice->strides[__pyx_v_i]); + + /* "View.MemoryView":1085 + * if mslice.shape[i] > 1: + * f_stride = mslice.strides[i] + * break # <<<<<<<<<<<<<< + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): + */ + goto __pyx_L7_break; + } + } + __pyx_L7_break:; + + /* "View.MemoryView":1087 + * break + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< + * return 'C' + * else: + */ + __pyx_t_2 = ((abs_py_ssize_t(__pyx_v_c_stride) <= abs_py_ssize_t(__pyx_v_f_stride)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1088 + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): + * return 'C' # <<<<<<<<<<<<<< + * else: + * return 'F' + */ + __pyx_r = 'C'; + goto __pyx_L0; + } + /*else*/ { + + /* "View.MemoryView":1090 + * return 'C' + * else: + * return 'F' # <<<<<<<<<<<<<< + * + * @cython.cdivision(True) + */ + __pyx_r = 'F'; + goto __pyx_L0; + } + + /* "View.MemoryView":1069 + * + * @cname('__pyx_get_best_slice_order') + * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< + * """ + * Figure out the best memory access order for a given slice. + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1093 + * + * @cython.cdivision(True) + * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< + * char *dst_data, Py_ssize_t *dst_strides, + * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, + */ + +static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v_src_strides, char *__pyx_v_dst_data, Py_ssize_t *__pyx_v_dst_strides, Py_ssize_t *__pyx_v_src_shape, Py_ssize_t *__pyx_v_dst_shape, int __pyx_v_ndim, size_t __pyx_v_itemsize) { + CYTHON_UNUSED Py_ssize_t __pyx_v_i; + CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent; + Py_ssize_t __pyx_v_dst_extent; + Py_ssize_t __pyx_v_src_stride; + Py_ssize_t __pyx_v_dst_stride; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + Py_ssize_t __pyx_t_4; + Py_ssize_t __pyx_t_5; + + /* "View.MemoryView":1100 + * + * cdef Py_ssize_t i + * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] + */ + __pyx_v_src_extent = (__pyx_v_src_shape[0]); + + /* "View.MemoryView":1101 + * cdef Py_ssize_t i + * cdef Py_ssize_t src_extent = src_shape[0] + * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t src_stride = src_strides[0] + * cdef Py_ssize_t dst_stride = dst_strides[0] + */ + __pyx_v_dst_extent = (__pyx_v_dst_shape[0]); + + /* "View.MemoryView":1102 + * cdef Py_ssize_t src_extent = src_shape[0] + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + */ + __pyx_v_src_stride = (__pyx_v_src_strides[0]); + + /* "View.MemoryView":1103 + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] + * cdef Py_ssize_t dst_stride = dst_strides[0] # <<<<<<<<<<<<<< + * + * if ndim == 1: + */ + __pyx_v_dst_stride = (__pyx_v_dst_strides[0]); + + /* "View.MemoryView":1105 + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + * if ndim == 1: # <<<<<<<<<<<<<< + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + */ + __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1106 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ + __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0); + if (__pyx_t_2) { + goto __pyx_L6_next_and; + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L5_bool_binop_done; + } + __pyx_L6_next_and:; + __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0); + if (__pyx_t_2) { + goto __pyx_L7_next_and; + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L5_bool_binop_done; + } + __pyx_L7_next_and:; + + /* "View.MemoryView":1107 + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< + * memcpy(dst_data, src_data, itemsize * dst_extent) + * else: + */ + __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize); + if (__pyx_t_2) { + __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride)); + } + __pyx_t_3 = (__pyx_t_2 != 0); + __pyx_t_1 = __pyx_t_3; + __pyx_L5_bool_binop_done:; + if (__pyx_t_1) { + + /* "View.MemoryView":1108 + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<< + * else: + * for i in range(dst_extent): + */ + memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent)); + goto __pyx_L4; + } + /*else*/ { + + /* "View.MemoryView":1110 + * memcpy(dst_data, src_data, itemsize * dst_extent) + * else: + * for i in range(dst_extent): # <<<<<<<<<<<<<< + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride + */ + __pyx_t_4 = __pyx_v_dst_extent; + for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { + __pyx_v_i = __pyx_t_5; + + /* "View.MemoryView":1111 + * else: + * for i in range(dst_extent): + * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<< + * src_data += src_stride + * dst_data += dst_stride + */ + memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize); + + /* "View.MemoryView":1112 + * for i in range(dst_extent): + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride # <<<<<<<<<<<<<< + * dst_data += dst_stride + * else: + */ + __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); + + /* "View.MemoryView":1113 + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride + * dst_data += dst_stride # <<<<<<<<<<<<<< + * else: + * for i in range(dst_extent): + */ + __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); + } + } + __pyx_L4:; + goto __pyx_L3; + } + /*else*/ { + + /* "View.MemoryView":1115 + * dst_data += dst_stride + * else: + * for i in range(dst_extent): # <<<<<<<<<<<<<< + * _copy_strided_to_strided(src_data, src_strides + 1, + * dst_data, dst_strides + 1, + */ + __pyx_t_4 = __pyx_v_dst_extent; + for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { + __pyx_v_i = __pyx_t_5; + + /* "View.MemoryView":1116 + * else: + * for i in range(dst_extent): + * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<< + * dst_data, dst_strides + 1, + * src_shape + 1, dst_shape + 1, + */ + _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize); + + /* "View.MemoryView":1120 + * src_shape + 1, dst_shape + 1, + * ndim - 1, itemsize) + * src_data += src_stride # <<<<<<<<<<<<<< + * dst_data += dst_stride + * + */ + __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); + + /* "View.MemoryView":1121 + * ndim - 1, itemsize) + * src_data += src_stride + * dst_data += dst_stride # <<<<<<<<<<<<<< + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, + */ + __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); + } + } + __pyx_L3:; + + /* "View.MemoryView":1093 + * + * @cython.cdivision(True) + * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< + * char *dst_data, Py_ssize_t *dst_strides, + * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, + */ + + /* function exit code */ +} + +/* "View.MemoryView":1123 + * dst_data += dst_stride + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + */ + +static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) { + + /* "View.MemoryView":1126 + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + * _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<< + * src.shape, dst.shape, ndim, itemsize) + * + */ + _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize); + + /* "View.MemoryView":1123 + * dst_data += dst_stride + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + */ + + /* function exit code */ +} + +/* "View.MemoryView":1130 + * + * @cname('__pyx_memoryview_slice_get_size') + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef int i + */ + +static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) { + int __pyx_v_i; + Py_ssize_t __pyx_v_size; + Py_ssize_t __pyx_r; + Py_ssize_t __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + + /* "View.MemoryView":1133 + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef int i + * cdef Py_ssize_t size = src.memview.view.itemsize # <<<<<<<<<<<<<< + * + * for i in range(ndim): + */ + __pyx_t_1 = __pyx_v_src->memview->view.itemsize; + __pyx_v_size = __pyx_t_1; + + /* "View.MemoryView":1135 + * cdef Py_ssize_t size = src.memview.view.itemsize + * + * for i in range(ndim): # <<<<<<<<<<<<<< + * size *= src.shape[i] + * + */ + __pyx_t_2 = __pyx_v_ndim; + for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { + __pyx_v_i = __pyx_t_3; + + /* "View.MemoryView":1136 + * + * for i in range(ndim): + * size *= src.shape[i] # <<<<<<<<<<<<<< + * + * return size + */ + __pyx_v_size = (__pyx_v_size * (__pyx_v_src->shape[__pyx_v_i])); + } + + /* "View.MemoryView":1138 + * size *= src.shape[i] + * + * return size # <<<<<<<<<<<<<< + * + * @cname('__pyx_fill_contig_strides_array') + */ + __pyx_r = __pyx_v_size; + goto __pyx_L0; + + /* "View.MemoryView":1130 + * + * @cname('__pyx_memoryview_slice_get_size') + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef int i + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1141 + * + * @cname('__pyx_fill_contig_strides_array') + * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< + * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride, + * int ndim, char order) nogil: + */ + +static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, Py_ssize_t __pyx_v_stride, int __pyx_v_ndim, char __pyx_v_order) { + int __pyx_v_idx; + Py_ssize_t __pyx_r; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + + /* "View.MemoryView":1150 + * cdef int idx + * + * if order == 'F': # <<<<<<<<<<<<<< + * for idx in range(ndim): + * strides[idx] = stride + */ + __pyx_t_1 = ((__pyx_v_order == 'F') != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1151 + * + * if order == 'F': + * for idx in range(ndim): # <<<<<<<<<<<<<< + * strides[idx] = stride + * stride = stride * shape[idx] + */ + __pyx_t_2 = __pyx_v_ndim; + for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { + __pyx_v_idx = __pyx_t_3; + + /* "View.MemoryView":1152 + * if order == 'F': + * for idx in range(ndim): + * strides[idx] = stride # <<<<<<<<<<<<<< + * stride = stride * shape[idx] + * else: + */ + (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; + + /* "View.MemoryView":1153 + * for idx in range(ndim): + * strides[idx] = stride + * stride = stride * shape[idx] # <<<<<<<<<<<<<< + * else: + * for idx in range(ndim - 1, -1, -1): + */ + __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); + } + goto __pyx_L3; + } + /*else*/ { + + /* "View.MemoryView":1155 + * stride = stride * shape[idx] + * else: + * for idx in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< + * strides[idx] = stride + * stride = stride * shape[idx] + */ + for (__pyx_t_2 = (__pyx_v_ndim - 1); __pyx_t_2 > -1; __pyx_t_2-=1) { + __pyx_v_idx = __pyx_t_2; + + /* "View.MemoryView":1156 + * else: + * for idx in range(ndim - 1, -1, -1): + * strides[idx] = stride # <<<<<<<<<<<<<< + * stride = stride * shape[idx] + * + */ + (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; + + /* "View.MemoryView":1157 + * for idx in range(ndim - 1, -1, -1): + * strides[idx] = stride + * stride = stride * shape[idx] # <<<<<<<<<<<<<< + * + * return stride + */ + __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); + } + } + __pyx_L3:; + + /* "View.MemoryView":1159 + * stride = stride * shape[idx] + * + * return stride # <<<<<<<<<<<<<< + * + * @cname('__pyx_memoryview_copy_data_to_temp') + */ + __pyx_r = __pyx_v_stride; + goto __pyx_L0; + + /* "View.MemoryView":1141 + * + * @cname('__pyx_fill_contig_strides_array') + * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< + * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride, + * int ndim, char order) nogil: + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1162 + * + * @cname('__pyx_memoryview_copy_data_to_temp') + * cdef void *copy_data_to_temp(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *tmpslice, + * char order, + */ + +static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_tmpslice, char __pyx_v_order, int __pyx_v_ndim) { + int __pyx_v_i; + void *__pyx_v_result; + size_t __pyx_v_itemsize; + size_t __pyx_v_size; + void *__pyx_r; + Py_ssize_t __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + struct __pyx_memoryview_obj *__pyx_t_4; + int __pyx_t_5; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; + + /* "View.MemoryView":1173 + * cdef void *result + * + * cdef size_t itemsize = src.memview.view.itemsize # <<<<<<<<<<<<<< + * cdef size_t size = slice_get_size(src, ndim) + * + */ + __pyx_t_1 = __pyx_v_src->memview->view.itemsize; + __pyx_v_itemsize = __pyx_t_1; + + /* "View.MemoryView":1174 + * + * cdef size_t itemsize = src.memview.view.itemsize + * cdef size_t size = slice_get_size(src, ndim) # <<<<<<<<<<<<<< + * + * result = malloc(size) + */ + __pyx_v_size = 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(__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_5; __pyx_t_3+=1) { + __pyx_v_i = __pyx_t_3; + + /* "View.MemoryView":1246 + * + * for i in range(ndim): + * if src.shape[i] != dst.shape[i]: # <<<<<<<<<<<<<< + * if src.shape[i] == 1: + * broadcasting = True + */ + __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) != (__pyx_v_dst.shape[__pyx_v_i])) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1247 + * for i in range(ndim): + * if src.shape[i] != dst.shape[i]: + * if src.shape[i] == 1: # <<<<<<<<<<<<<< + * broadcasting = True + * src.strides[i] = 0 + */ + __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) == 1) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1248 + * if src.shape[i] != dst.shape[i]: + * if src.shape[i] == 1: + * broadcasting = True # <<<<<<<<<<<<<< + * src.strides[i] = 0 + * else: + */ + __pyx_v_broadcasting = 1; + + /* "View.MemoryView":1249 + * if src.shape[i] == 1: + * broadcasting = True + * src.strides[i] = 0 # <<<<<<<<<<<<<< + * else: + * _err_extents(i, dst.shape[i], src.shape[i]) + */ + (__pyx_v_src.strides[__pyx_v_i]) = 0; + goto __pyx_L7; + } + /*else*/ { + + /* "View.MemoryView":1251 + * src.strides[i] = 0 + * else: + * _err_extents(i, dst.shape[i], src.shape[i]) # <<<<<<<<<<<<<< + * + * if src.suboffsets[i] >= 0: + */ + __pyx_t_4 = __pyx_memoryview_err_extents(__pyx_v_i, (__pyx_v_dst.shape[__pyx_v_i]), (__pyx_v_src.shape[__pyx_v_i])); if (unlikely(__pyx_t_4 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1251; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + } + __pyx_L7:; + goto __pyx_L6; + } + __pyx_L6:; + + /* "View.MemoryView":1253 + * _err_extents(i, dst.shape[i], src.shape[i]) + * + * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< + * _err_dim(ValueError, "Dimension %d is not direct", i) + * + */ + __pyx_t_2 = (((__pyx_v_src.suboffsets[__pyx_v_i]) >= 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1254 + * + * if src.suboffsets[i] >= 0: + * _err_dim(ValueError, "Dimension %d is not direct", i) # <<<<<<<<<<<<<< + * + * if 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"View.MemoryView":1259 + * + * if not slice_is_contig(&src, order, ndim): + * order = get_best_order(&dst, ndim) # <<<<<<<<<<<<<< + * + * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) + */ + __pyx_v_order = __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim); + goto __pyx_L10; + } + __pyx_L10:; + + /* "View.MemoryView":1261 + * order = get_best_order(&dst, ndim) + * + * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) # <<<<<<<<<<<<<< + * src = tmp + * + */ + __pyx_t_6 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_6 == NULL)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1261; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_v_tmpdata = __pyx_t_6; + + /* "View.MemoryView":1262 + * + * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) + * src = tmp # <<<<<<<<<<<<<< + * + * if not broadcasting: + */ + __pyx_v_src = __pyx_v_tmp; + goto __pyx_L9; + } + __pyx_L9:; + + /* "View.MemoryView":1264 + * src = tmp + * + * if not broadcasting: # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_2 = ((!(__pyx_v_broadcasting != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1267 + * + * + * if slice_is_contig(&src, 'C', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(&dst, 'C', ndim) + * elif slice_is_contig(&src, 'F', ndim): + */ + __pyx_t_2 = (__pyx_memviewslice_is_contig((&__pyx_v_src), 'C', __pyx_v_ndim) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1268 + * + * if slice_is_contig(&src, 'C', ndim): + * direct_copy = slice_is_contig(&dst, 'C', ndim) # <<<<<<<<<<<<<< + * elif slice_is_contig(&src, 'F', ndim): + * direct_copy = slice_is_contig(&dst, 'F', ndim) + */ + __pyx_v_direct_copy = __pyx_memviewslice_is_contig((&__pyx_v_dst), 'C', __pyx_v_ndim); + goto __pyx_L12; + } + + /* "View.MemoryView":1269 + * if slice_is_contig(&src, 'C', ndim): + * direct_copy = slice_is_contig(&dst, 'C', ndim) + * elif slice_is_contig(&src, 'F', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(&dst, 'F', ndim) + * + */ + __pyx_t_2 = (__pyx_memviewslice_is_contig((&__pyx_v_src), 'F', __pyx_v_ndim) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1270 + * direct_copy = slice_is_contig(&dst, 'C', ndim) + * elif slice_is_contig(&src, 'F', ndim): + * direct_copy = slice_is_contig(&dst, 'F', ndim) # <<<<<<<<<<<<<< + * + * if direct_copy: + */ + __pyx_v_direct_copy = __pyx_memviewslice_is_contig((&__pyx_v_dst), 'F', __pyx_v_ndim); + goto __pyx_L12; + } + __pyx_L12:; + + /* "View.MemoryView":1272 + * direct_copy = slice_is_contig(&dst, 'F', ndim) + * + * if direct_copy: # <<<<<<<<<<<<<< + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + */ + __pyx_t_2 = (__pyx_v_direct_copy != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1274 + * if direct_copy: + * + * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); + + /* "View.MemoryView":1275 + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) # <<<<<<<<<<<<<< + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) + */ + memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim)); + + /* "View.MemoryView":1276 + * refcount_copying(&dst, dtype_is_object, ndim, False) + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< + * free(tmpdata) + * return 0 + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); + + /* "View.MemoryView":1277 + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) # <<<<<<<<<<<<<< + * return 0 + * + */ + free(__pyx_v_tmpdata); + + /* "View.MemoryView":1278 + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) + * return 0 # <<<<<<<<<<<<<< + * + * if order == 'F' == get_best_order(&dst, ndim): + */ + __pyx_r = 0; + goto __pyx_L0; + } + goto __pyx_L11; + } + __pyx_L11:; + + /* "View.MemoryView":1280 + * return 0 + * + * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_2 = (__pyx_v_order == 'F'); + if (__pyx_t_2) { + __pyx_t_2 = ('F' == __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim)); + } + __pyx_t_7 = (__pyx_t_2 != 0); + if (__pyx_t_7) { + + /* "View.MemoryView":1283 + * + * + * transpose_memslice(&src) # <<<<<<<<<<<<<< + * transpose_memslice(&dst) + * + */ + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1283; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "View.MemoryView":1284 + * + * transpose_memslice(&src) + * transpose_memslice(&dst) # <<<<<<<<<<<<<< + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + */ + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_dst)); if (unlikely(__pyx_t_5 == 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1284; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + goto __pyx_L14; + } + __pyx_L14:; + + /* "View.MemoryView":1286 + * transpose_memslice(&dst) + * + * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< + * copy_strided_to_strided(&src, &dst, ndim, itemsize) + * refcount_copying(&dst, dtype_is_object, ndim, True) + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); + + /* "View.MemoryView":1287 + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + * copy_strided_to_strided(&src, &dst, ndim, itemsize) # <<<<<<<<<<<<<< + * refcount_copying(&dst, dtype_is_object, ndim, True) + * + */ + copy_strided_to_strided((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize); + 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PyInt_FromSsize_t(i); if(!x) return 0; + r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); + Py_DECREF(x); + return r; +} + +static int __pyx_mp_ass_subscript_array(PyObject *o, PyObject *i, PyObject *v) { + if (v) { + return __pyx_array___setitem__(o, i, v); + } + else { + PyErr_Format(PyExc_NotImplementedError, + "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name); + return -1; + } +} + +static PyObject *__pyx_tp_getattro_array(PyObject *o, PyObject *n) { + PyObject *v = PyObject_GenericGetAttr(o, n); + if (!v && PyErr_ExceptionMatches(PyExc_AttributeError)) { + PyErr_Clear(); + v = __pyx_array___getattr__(o, n); + } + return v; +} + +static PyObject *__pyx_getprop___pyx_array_memview(PyObject *o, CYTHON_UNUSED void *x) { + return get_memview(o); +} + +static PyMethodDef __pyx_methods_array[] = { + {"__getattr__", (PyCFunction)__pyx_array___getattr__, METH_O|METH_COEXIST, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets_array[] = { + {(char *)"memview", __pyx_getprop___pyx_array_memview, 0, 0, 0}, + {0, 0, 0, 0, 0} +}; + +static PySequenceMethods __pyx_tp_as_sequence_array = { + 0, /*sq_length*/ + 0, /*sq_concat*/ + 0, /*sq_repeat*/ + __pyx_sq_item_array, /*sq_item*/ + 0, /*sq_slice*/ + 0, /*sq_ass_item*/ + 0, /*sq_ass_slice*/ + 0, /*sq_contains*/ + 0, /*sq_inplace_concat*/ + 0, /*sq_inplace_repeat*/ +}; + +static PyMappingMethods __pyx_tp_as_mapping_array = { + 0, /*mp_length*/ + __pyx_array___getitem__, /*mp_subscript*/ + __pyx_mp_ass_subscript_array, /*mp_ass_subscript*/ +}; + +static PyBufferProcs __pyx_tp_as_buffer_array = { + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getreadbuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getwritebuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getsegcount*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getcharbuffer*/ + #endif + __pyx_array_getbuffer, /*bf_getbuffer*/ + 0, /*bf_releasebuffer*/ +}; + +static PyTypeObject __pyx_type___pyx_array = { + PyVarObject_HEAD_INIT(0, 0) + "GPy.util.choleskies_cython.array", /*tp_name*/ + sizeof(struct __pyx_array_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_array, /*tp_dealloc*/ + 0, /*tp_print*/ + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #else + 0, /*reserved*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + &__pyx_tp_as_sequence_array, /*tp_as_sequence*/ + &__pyx_tp_as_mapping_array, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + __pyx_tp_getattro_array, /*tp_getattro*/ + 0, /*tp_setattro*/ + &__pyx_tp_as_buffer_array, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ + 0, /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_array, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets_array, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_array, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif +}; + +static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { + struct __pyx_MemviewEnum_obj *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_MemviewEnum_obj *)o); + p->name = Py_None; Py_INCREF(Py_None); + return o; +} + +static void __pyx_tp_dealloc_Enum(PyObject *o) { + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + #if PY_VERSION_HEX >= 0x030400a1 + if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + Py_CLEAR(p->name); + (*Py_TYPE(o)->tp_free)(o); +} + +static int __pyx_tp_traverse_Enum(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + if (p->name) { + e = (*v)(p->name, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear_Enum(PyObject *o) { + PyObject* tmp; + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + tmp = ((PyObject*)p->name); + p->name = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + return 0; +} + +static PyMethodDef __pyx_methods_Enum[] = { + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type___pyx_MemviewEnum = { + PyVarObject_HEAD_INIT(0, 0) + "GPy.util.choleskies_cython.Enum", /*tp_name*/ + sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_Enum, /*tp_dealloc*/ + 0, /*tp_print*/ + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #else + 0, /*reserved*/ + #endif + __pyx_MemviewEnum___repr__, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + 0, /*tp_doc*/ + __pyx_tp_traverse_Enum, /*tp_traverse*/ + __pyx_tp_clear_Enum, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_Enum, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + __pyx_MemviewEnum___init__, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_Enum, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif +}; +static struct __pyx_vtabstruct_memoryview __pyx_vtable_memoryview; + +static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_memoryview_obj *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_memoryview_obj *)o); + p->__pyx_vtab = __pyx_vtabptr_memoryview; + p->obj = Py_None; Py_INCREF(Py_None); + p->_size = Py_None; Py_INCREF(Py_None); + p->_array_interface = Py_None; Py_INCREF(Py_None); + p->view.obj = NULL; + if (unlikely(__pyx_memoryview___cinit__(o, a, k) < 0)) { + Py_DECREF(o); o = 0; + } + return o; +} + +static void __pyx_tp_dealloc_memoryview(PyObject *o) { + struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; + #if PY_VERSION_HEX >= 0x030400a1 + if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + ++Py_REFCNT(o); + __pyx_memoryview___dealloc__(o); + --Py_REFCNT(o); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->obj); + Py_CLEAR(p->_size); + Py_CLEAR(p->_array_interface); + (*Py_TYPE(o)->tp_free)(o); +} + +static int __pyx_tp_traverse_memoryview(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; + if (p->obj) { + e = (*v)(p->obj, a); if (e) return e; + } + if (p->_size) { + e = (*v)(p->_size, a); if (e) return e; + } + if (p->_array_interface) { + e = (*v)(p->_array_interface, a); if (e) return e; + } + if (p->view.obj) { + e = (*v)(p->view.obj, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear_memoryview(PyObject *o) { + PyObject* tmp; + struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; + tmp = ((PyObject*)p->obj); + p->obj = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + tmp = ((PyObject*)p->_size); + p->_size = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + tmp = ((PyObject*)p->_array_interface); + p->_array_interface = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + Py_CLEAR(p->view.obj); + return 0; +} +static PyObject *__pyx_sq_item_memoryview(PyObject *o, Py_ssize_t i) { + PyObject *r; + PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0; + r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); + Py_DECREF(x); + return r; +} + +static int __pyx_mp_ass_subscript_memoryview(PyObject *o, PyObject *i, PyObject *v) { + if (v) { + return __pyx_memoryview___setitem__(o, i, v); + } + else { + PyErr_Format(PyExc_NotImplementedError, + "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name); + return -1; + } +} + +static PyObject *__pyx_getprop___pyx_memoryview_T(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryview_transpose(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_base(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryview__get__base(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_shape(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryview_get_shape(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_strides(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryview_get_strides(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_suboffsets(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryview_get_suboffsets(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_ndim(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryview_get_ndim(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_itemsize(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryview_get_itemsize(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_nbytes(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryview_get_nbytes(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_size(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryview_get_size(o); +} + +static PyMethodDef __pyx_methods_memoryview[] = { + {"is_c_contig", (PyCFunction)__pyx_memoryview_is_c_contig, METH_NOARGS, 0}, + {"is_f_contig", (PyCFunction)__pyx_memoryview_is_f_contig, METH_NOARGS, 0}, + {"copy", (PyCFunction)__pyx_memoryview_copy, METH_NOARGS, 0}, + {"copy_fortran", (PyCFunction)__pyx_memoryview_copy_fortran, METH_NOARGS, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets_memoryview[] = { + {(char *)"T", __pyx_getprop___pyx_memoryview_T, 0, 0, 0}, + {(char *)"base", __pyx_getprop___pyx_memoryview_base, 0, 0, 0}, + {(char *)"shape", __pyx_getprop___pyx_memoryview_shape, 0, 0, 0}, + {(char *)"strides", __pyx_getprop___pyx_memoryview_strides, 0, 0, 0}, + {(char *)"suboffsets", __pyx_getprop___pyx_memoryview_suboffsets, 0, 0, 0}, + {(char *)"ndim", __pyx_getprop___pyx_memoryview_ndim, 0, 0, 0}, + {(char *)"itemsize", __pyx_getprop___pyx_memoryview_itemsize, 0, 0, 0}, + {(char *)"nbytes", __pyx_getprop___pyx_memoryview_nbytes, 0, 0, 0}, + {(char *)"size", __pyx_getprop___pyx_memoryview_size, 0, 0, 0}, + {0, 0, 0, 0, 0} +}; + +static PySequenceMethods __pyx_tp_as_sequence_memoryview = { + __pyx_memoryview___len__, /*sq_length*/ + 0, /*sq_concat*/ + 0, /*sq_repeat*/ + __pyx_sq_item_memoryview, /*sq_item*/ + 0, /*sq_slice*/ + 0, /*sq_ass_item*/ + 0, /*sq_ass_slice*/ + 0, /*sq_contains*/ + 0, /*sq_inplace_concat*/ + 0, /*sq_inplace_repeat*/ +}; + +static PyMappingMethods __pyx_tp_as_mapping_memoryview = { + __pyx_memoryview___len__, /*mp_length*/ + __pyx_memoryview___getitem__, /*mp_subscript*/ + __pyx_mp_ass_subscript_memoryview, /*mp_ass_subscript*/ +}; + +static PyBufferProcs __pyx_tp_as_buffer_memoryview = { + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getreadbuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getwritebuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getsegcount*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getcharbuffer*/ + #endif + __pyx_memoryview_getbuffer, /*bf_getbuffer*/ + 0, /*bf_releasebuffer*/ +}; + +static PyTypeObject __pyx_type___pyx_memoryview = { + PyVarObject_HEAD_INIT(0, 0) + "GPy.util.choleskies_cython.memoryview", /*tp_name*/ + sizeof(struct __pyx_memoryview_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_memoryview, /*tp_dealloc*/ + 0, /*tp_print*/ + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #else + 0, /*reserved*/ + #endif + __pyx_memoryview___repr__, /*tp_repr*/ + 0, /*tp_as_number*/ + &__pyx_tp_as_sequence_memoryview, /*tp_as_sequence*/ + &__pyx_tp_as_mapping_memoryview, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + __pyx_memoryview___str__, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + &__pyx_tp_as_buffer_memoryview, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + 0, /*tp_doc*/ + __pyx_tp_traverse_memoryview, /*tp_traverse*/ + __pyx_tp_clear_memoryview, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_memoryview, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets_memoryview, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_memoryview, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif +}; +static struct __pyx_vtabstruct__memoryviewslice __pyx_vtable__memoryviewslice; + +static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_memoryviewslice_obj *p; + PyObject *o = __pyx_tp_new_memoryview(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_memoryviewslice_obj *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_memoryview*)__pyx_vtabptr__memoryviewslice; + p->from_object = Py_None; Py_INCREF(Py_None); + p->from_slice.memview = NULL; + return o; +} + +static void __pyx_tp_dealloc__memoryviewslice(PyObject *o) { + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + #if PY_VERSION_HEX >= 0x030400a1 + if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + ++Py_REFCNT(o); + __pyx_memoryviewslice___dealloc__(o); + --Py_REFCNT(o); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->from_object); + PyObject_GC_Track(o); + __pyx_tp_dealloc_memoryview(o); +} + +static int __pyx_tp_traverse__memoryviewslice(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + e = __pyx_tp_traverse_memoryview(o, v, a); if (e) return e; + if (p->from_object) { + e = (*v)(p->from_object, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear__memoryviewslice(PyObject *o) { + PyObject* tmp; + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + __pyx_tp_clear_memoryview(o); + tmp = ((PyObject*)p->from_object); + p->from_object = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + __PYX_XDEC_MEMVIEW(&p->from_slice, 1); + return 0; +} + +static PyObject *__pyx_getprop___pyx_memoryviewslice_base(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_memoryviewslice__get__base(o); +} + +static PyMethodDef __pyx_methods__memoryviewslice[] = { + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets__memoryviewslice[] = { + {(char *)"base", __pyx_getprop___pyx_memoryviewslice_base, 0, 0, 0}, + {0, 0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type___pyx_memoryviewslice = { + PyVarObject_HEAD_INIT(0, 0) + "GPy.util.choleskies_cython._memoryviewslice", /*tp_name*/ + sizeof(struct __pyx_memoryviewslice_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc__memoryviewslice, /*tp_dealloc*/ + 0, /*tp_print*/ + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #else + 0, /*reserved*/ + #endif + #if CYTHON_COMPILING_IN_PYPY + __pyx_memoryview___repr__, /*tp_repr*/ + #else + 0, /*tp_repr*/ + #endif + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + #if CYTHON_COMPILING_IN_PYPY + __pyx_memoryview___str__, /*tp_str*/ + #else + 0, /*tp_str*/ + #endif + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + "Internal class for passing memoryview slices to Python", /*tp_doc*/ + __pyx_tp_traverse__memoryviewslice, /*tp_traverse*/ + __pyx_tp_clear__memoryviewslice, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods__memoryviewslice, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets__memoryviewslice, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new__memoryviewslice, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif +}; + static PyMethodDef __pyx_methods[] = { {0, 0, 0, 0} 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{&__pyx_n_s_MemoryError, __pyx_k_MemoryError, sizeof(__pyx_k_MemoryError), 0, 0, 1, 1}, + {&__pyx_kp_s_MemoryView_of_r_at_0x_x, __pyx_k_MemoryView_of_r_at_0x_x, sizeof(__pyx_k_MemoryView_of_r_at_0x_x), 0, 0, 1, 0}, + {&__pyx_kp_s_MemoryView_of_r_object, __pyx_k_MemoryView_of_r_object, sizeof(__pyx_k_MemoryView_of_r_object), 0, 0, 1, 0}, {&__pyx_n_s_N, __pyx_k_N, sizeof(__pyx_k_N), 0, 0, 1, 1}, {&__pyx_kp_u_Non_native_byte_order_not_suppor, __pyx_k_Non_native_byte_order_not_suppor, sizeof(__pyx_k_Non_native_byte_order_not_suppor), 0, 1, 0, 0}, + {&__pyx_n_b_O, __pyx_k_O, sizeof(__pyx_k_O), 0, 0, 0, 1}, + {&__pyx_kp_s_Out_of_bounds_on_buffer_access_a, __pyx_k_Out_of_bounds_on_buffer_access_a, sizeof(__pyx_k_Out_of_bounds_on_buffer_access_a), 0, 0, 1, 0}, {&__pyx_n_s_RuntimeError, __pyx_k_RuntimeError, sizeof(__pyx_k_RuntimeError), 0, 0, 1, 1}, + {&__pyx_n_s_TypeError, __pyx_k_TypeError, sizeof(__pyx_k_TypeError), 0, 0, 1, 1}, + {&__pyx_kp_s_Unable_to_convert_item_to_object, __pyx_k_Unable_to_convert_item_to_object, sizeof(__pyx_k_Unable_to_convert_item_to_object), 0, 0, 1, 0}, {&__pyx_n_s_ValueError, __pyx_k_ValueError, sizeof(__pyx_k_ValueError), 0, 0, 1, 1}, + {&__pyx_n_s_allocate_buffer, __pyx_k_allocate_buffer, sizeof(__pyx_k_allocate_buffer), 0, 0, 1, 1}, {&__pyx_n_s_backprop_gradient, __pyx_k_backprop_gradient, sizeof(__pyx_k_backprop_gradient), 0, 0, 1, 1}, + {&__pyx_n_s_backprop_gradient_par, __pyx_k_backprop_gradient_par, sizeof(__pyx_k_backprop_gradient_par), 0, 0, 1, 1}, + {&__pyx_n_s_backprop_gradient_par_c, __pyx_k_backprop_gradient_par_c, sizeof(__pyx_k_backprop_gradient_par_c), 0, 0, 1, 1}, + {&__pyx_n_s_base, __pyx_k_base, sizeof(__pyx_k_base), 0, 0, 1, 1}, + {&__pyx_n_s_c, __pyx_k_c, sizeof(__pyx_k_c), 0, 0, 1, 1}, + {&__pyx_n_u_c, __pyx_k_c, sizeof(__pyx_k_c), 0, 1, 0, 1}, + {&__pyx_n_s_class, __pyx_k_class, sizeof(__pyx_k_class), 0, 0, 1, 1}, + {&__pyx_kp_s_contiguous_and_direct, __pyx_k_contiguous_and_direct, sizeof(__pyx_k_contiguous_and_direct), 0, 0, 1, 0}, + {&__pyx_kp_s_contiguous_and_indirect, __pyx_k_contiguous_and_indirect, sizeof(__pyx_k_contiguous_and_indirect), 0, 0, 1, 0}, {&__pyx_n_s_copy, __pyx_k_copy, sizeof(__pyx_k_copy), 0, 0, 1, 1}, {&__pyx_n_s_count, __pyx_k_count, sizeof(__pyx_k_count), 0, 0, 1, 1}, {&__pyx_n_s_d, __pyx_k_d, sizeof(__pyx_k_d), 0, 0, 1, 1}, {&__pyx_n_s_dL, __pyx_k_dL, sizeof(__pyx_k_dL), 0, 0, 1, 1}, {&__pyx_n_s_dL_dK, __pyx_k_dL_dK, sizeof(__pyx_k_dL_dK), 0, 0, 1, 1}, + {&__pyx_n_s_dtype_is_object, __pyx_k_dtype_is_object, sizeof(__pyx_k_dtype_is_object), 0, 0, 1, 1}, {&__pyx_n_s_empty, __pyx_k_empty, sizeof(__pyx_k_empty), 0, 0, 1, 1}, + {&__pyx_n_s_enumerate, __pyx_k_enumerate, sizeof(__pyx_k_enumerate), 0, 0, 1, 1}, + {&__pyx_n_s_error, __pyx_k_error, sizeof(__pyx_k_error), 0, 0, 1, 1}, + {&__pyx_n_s_flags, __pyx_k_flags, sizeof(__pyx_k_flags), 0, 0, 1, 1}, {&__pyx_n_s_flat, __pyx_k_flat, sizeof(__pyx_k_flat), 0, 0, 1, 1}, {&__pyx_n_s_flat_to_triang, __pyx_k_flat_to_triang, sizeof(__pyx_k_flat_to_triang), 0, 0, 1, 1}, + {&__pyx_n_s_format, __pyx_k_format, sizeof(__pyx_k_format), 0, 0, 1, 1}, + {&__pyx_n_s_fortran, __pyx_k_fortran, sizeof(__pyx_k_fortran), 0, 0, 1, 1}, + {&__pyx_n_u_fortran, __pyx_k_fortran, sizeof(__pyx_k_fortran), 0, 1, 0, 1}, + {&__pyx_kp_s_got_differing_extents_in_dimensi, __pyx_k_got_differing_extents_in_dimensi, sizeof(__pyx_k_got_differing_extents_in_dimensi), 0, 0, 1, 0}, {&__pyx_kp_s_home_james_work_GPy_GPy_util_ch, __pyx_k_home_james_work_GPy_GPy_util_ch, sizeof(__pyx_k_home_james_work_GPy_GPy_util_ch), 0, 0, 1, 0}, {&__pyx_n_s_i, __pyx_k_i, sizeof(__pyx_k_i), 0, 0, 1, 1}, + {&__pyx_n_s_id, __pyx_k_id, sizeof(__pyx_k_id), 0, 0, 1, 1}, {&__pyx_n_s_import, __pyx_k_import, sizeof(__pyx_k_import), 0, 0, 1, 1}, + {&__pyx_n_s_itemsize, __pyx_k_itemsize, sizeof(__pyx_k_itemsize), 0, 0, 1, 1}, + {&__pyx_kp_s_itemsize_0_for_cython_array, __pyx_k_itemsize_0_for_cython_array, sizeof(__pyx_k_itemsize_0_for_cython_array), 0, 0, 1, 0}, {&__pyx_n_s_j, __pyx_k_j, sizeof(__pyx_k_j), 0, 0, 1, 1}, {&__pyx_n_s_k, __pyx_k_k, sizeof(__pyx_k_k), 0, 0, 1, 1}, {&__pyx_n_s_m, __pyx_k_m, sizeof(__pyx_k_m), 0, 0, 1, 1}, {&__pyx_n_s_main, __pyx_k_main, sizeof(__pyx_k_main), 0, 0, 1, 1}, + {&__pyx_n_s_memview, __pyx_k_memview, sizeof(__pyx_k_memview), 0, 0, 1, 1}, {&__pyx_n_s_mm, __pyx_k_mm, sizeof(__pyx_k_mm), 0, 0, 1, 1}, + {&__pyx_n_s_mode, __pyx_k_mode, sizeof(__pyx_k_mode), 0, 0, 1, 1}, + {&__pyx_n_s_name, __pyx_k_name, sizeof(__pyx_k_name), 0, 0, 1, 1}, + {&__pyx_n_s_name_2, __pyx_k_name_2, sizeof(__pyx_k_name_2), 0, 0, 1, 1}, {&__pyx_kp_u_ndarray_is_not_C_contiguous, __pyx_k_ndarray_is_not_C_contiguous, sizeof(__pyx_k_ndarray_is_not_C_contiguous), 0, 1, 0, 0}, {&__pyx_kp_u_ndarray_is_not_Fortran_contiguou, __pyx_k_ndarray_is_not_Fortran_contiguou, sizeof(__pyx_k_ndarray_is_not_Fortran_contiguou), 0, 1, 0, 0}, + {&__pyx_n_s_ndim, __pyx_k_ndim, sizeof(__pyx_k_ndim), 0, 0, 1, 1}, {&__pyx_n_s_np, __pyx_k_np, sizeof(__pyx_k_np), 0, 0, 1, 1}, {&__pyx_n_s_numpy, __pyx_k_numpy, sizeof(__pyx_k_numpy), 0, 0, 1, 1}, + {&__pyx_n_s_obj, __pyx_k_obj, sizeof(__pyx_k_obj), 0, 0, 1, 1}, + {&__pyx_n_s_pack, __pyx_k_pack, sizeof(__pyx_k_pack), 0, 0, 1, 1}, + {&__pyx_n_s_pyx_getbuffer, __pyx_k_pyx_getbuffer, sizeof(__pyx_k_pyx_getbuffer), 0, 0, 1, 1}, + {&__pyx_n_s_pyx_vtable, __pyx_k_pyx_vtable, sizeof(__pyx_k_pyx_vtable), 0, 0, 1, 1}, {&__pyx_n_s_range, __pyx_k_range, sizeof(__pyx_k_range), 0, 0, 1, 1}, {&__pyx_n_s_ret, __pyx_k_ret, sizeof(__pyx_k_ret), 0, 0, 1, 1}, + {&__pyx_n_s_shape, __pyx_k_shape, sizeof(__pyx_k_shape), 0, 0, 1, 1}, + {&__pyx_n_s_size, __pyx_k_size, sizeof(__pyx_k_size), 0, 0, 1, 1}, + {&__pyx_n_s_start, __pyx_k_start, sizeof(__pyx_k_start), 0, 0, 1, 1}, + {&__pyx_n_s_step, __pyx_k_step, sizeof(__pyx_k_step), 0, 0, 1, 1}, + {&__pyx_n_s_stop, __pyx_k_stop, sizeof(__pyx_k_stop), 0, 0, 1, 1}, + {&__pyx_kp_s_strided_and_direct, __pyx_k_strided_and_direct, sizeof(__pyx_k_strided_and_direct), 0, 0, 1, 0}, + {&__pyx_kp_s_strided_and_direct_or_indirect, __pyx_k_strided_and_direct_or_indirect, sizeof(__pyx_k_strided_and_direct_or_indirect), 0, 0, 1, 0}, + {&__pyx_kp_s_strided_and_indirect, __pyx_k_strided_and_indirect, sizeof(__pyx_k_strided_and_indirect), 0, 0, 1, 0}, + {&__pyx_n_s_struct, __pyx_k_struct, sizeof(__pyx_k_struct), 0, 0, 1, 1}, {&__pyx_n_s_test, __pyx_k_test, sizeof(__pyx_k_test), 0, 0, 1, 1}, {&__pyx_n_s_triang_to_flat, __pyx_k_triang_to_flat, sizeof(__pyx_k_triang_to_flat), 0, 0, 1, 1}, {&__pyx_n_s_tril, __pyx_k_tril, sizeof(__pyx_k_tril), 0, 0, 1, 1}, + {&__pyx_kp_s_unable_to_allocate_array_data, __pyx_k_unable_to_allocate_array_data, sizeof(__pyx_k_unable_to_allocate_array_data), 0, 0, 1, 0}, + {&__pyx_kp_s_unable_to_allocate_shape_and_str, __pyx_k_unable_to_allocate_shape_and_str, sizeof(__pyx_k_unable_to_allocate_shape_and_str), 0, 0, 1, 0}, {&__pyx_kp_u_unknown_dtype_code_in_numpy_pxd, __pyx_k_unknown_dtype_code_in_numpy_pxd, sizeof(__pyx_k_unknown_dtype_code_in_numpy_pxd), 0, 1, 0, 0}, + {&__pyx_n_s_unpack, __pyx_k_unpack, sizeof(__pyx_k_unpack), 0, 0, 1, 1}, + {&__pyx_n_s_xrange, __pyx_k_xrange, sizeof(__pyx_k_xrange), 0, 0, 1, 1}, {&__pyx_n_s_zeros, __pyx_k_zeros, sizeof(__pyx_k_zeros), 0, 0, 1, 1}, {0, 0, 0, 0, 0, 0, 0} }; static int __Pyx_InitCachedBuiltins(void) { - __pyx_builtin_range = __Pyx_GetBuiltinName(__pyx_n_s_range); if (!__pyx_builtin_range) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 22; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_range = __Pyx_GetBuiltinName(__pyx_n_s_range); if (!__pyx_builtin_range) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 23; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_builtin_ValueError = __Pyx_GetBuiltinName(__pyx_n_s_ValueError); if (!__pyx_builtin_ValueError) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_builtin_RuntimeError = __Pyx_GetBuiltinName(__pyx_n_s_RuntimeError); if (!__pyx_builtin_RuntimeError) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_MemoryError = __Pyx_GetBuiltinName(__pyx_n_s_MemoryError); if (!__pyx_builtin_MemoryError) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 142; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_enumerate = __Pyx_GetBuiltinName(__pyx_n_s_enumerate); if (!__pyx_builtin_enumerate) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_Ellipsis = __Pyx_GetBuiltinName(__pyx_n_s_Ellipsis); if (!__pyx_builtin_Ellipsis) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 357; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_TypeError = __Pyx_GetBuiltinName(__pyx_n_s_TypeError); if (!__pyx_builtin_TypeError) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 386; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #if PY_MAJOR_VERSION >= 3 + __pyx_builtin_xrange = __Pyx_GetBuiltinName(__pyx_n_s_range); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 514; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #else + __pyx_builtin_xrange = __Pyx_GetBuiltinName(__pyx_n_s_xrange); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 514; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + #endif + __pyx_builtin_id = __Pyx_GetBuiltinName(__pyx_n_s_id); if (!__pyx_builtin_id) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 569; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_IndexError = __Pyx_GetBuiltinName(__pyx_n_s_IndexError); if (!__pyx_builtin_IndexError) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 789; __pyx_clineno = __LINE__; goto __pyx_L1_error;} return 0; __pyx_L1_error:; return -1; @@ -4377,41 +17048,241 @@ static int __Pyx_InitCachedConstants(void) { __Pyx_GOTREF(__pyx_tuple__6); __Pyx_GIVEREF(__pyx_tuple__6); - /* "GPy/util/choleskies_cython.pyx":10 + /* "View.MemoryView":127 + * + * if not self.ndim: + * raise ValueError("Empty shape tuple for cython.array") # <<<<<<<<<<<<<< + * + * if itemsize <= 0: + */ + __pyx_tuple__7 = PyTuple_Pack(1, __pyx_kp_s_Empty_shape_tuple_for_cython_arr); if (unlikely(!__pyx_tuple__7)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 127; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__7); + __Pyx_GIVEREF(__pyx_tuple__7); + + /* "View.MemoryView":130 + * + * if itemsize <= 0: + * raise ValueError("itemsize <= 0 for cython.array") # <<<<<<<<<<<<<< + * + * if isinstance(format, unicode): + */ + __pyx_tuple__8 = PyTuple_Pack(1, __pyx_kp_s_itemsize_0_for_cython_array); if (unlikely(!__pyx_tuple__8)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 130; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__8); + __Pyx_GIVEREF(__pyx_tuple__8); + + /* "View.MemoryView":142 + * + * if not self._shape: + * raise MemoryError("unable to allocate shape and strides.") # <<<<<<<<<<<<<< + * + * + */ + __pyx_tuple__9 = PyTuple_Pack(1, __pyx_kp_s_unable_to_allocate_shape_and_str); if (unlikely(!__pyx_tuple__9)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 142; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__9); + __Pyx_GIVEREF(__pyx_tuple__9); + + /* "View.MemoryView":170 + * self.data = malloc(self.len) + * if not self.data: + * raise MemoryError("unable to allocate array data.") # <<<<<<<<<<<<<< + * + * if self.dtype_is_object: + */ + __pyx_tuple__10 = PyTuple_Pack(1, __pyx_kp_s_unable_to_allocate_array_data); if (unlikely(!__pyx_tuple__10)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 170; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__10); + __Pyx_GIVEREF(__pyx_tuple__10); + + /* "View.MemoryView":186 + * bufmode = PyBUF_F_CONTIGUOUS | PyBUF_ANY_CONTIGUOUS + * if not (flags & bufmode): + * raise ValueError("Can only create a buffer that is contiguous in memory.") # <<<<<<<<<<<<<< + * info.buf = 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__Pyx_GOTREF(__pyx_tuple__31); + __Pyx_GIVEREF(__pyx_tuple__31); + + /* "View.MemoryView":282 + * + * cdef contiguous = Enum("") + * cdef indirect_contiguous = Enum("") # <<<<<<<<<<<<<< + * + * + */ + __pyx_tuple__32 = PyTuple_Pack(1, __pyx_kp_s_contiguous_and_indirect); if (unlikely(!__pyx_tuple__32)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__32); + __Pyx_GIVEREF(__pyx_tuple__32); __Pyx_RefNannyFinishContext(); return 0; __pyx_L1_error:; @@ -4420,7 +17291,17 @@ static int __Pyx_InitCachedConstants(void) { } static int __Pyx_InitGlobals(void) { + /* InitThreads.init */ + #ifdef WITH_THREAD +PyEval_InitThreads(); +#endif + +if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (__Pyx_InitStrings(__pyx_string_tab) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}; + __pyx_int_0 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__pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_ptype_5numpy_flatiter = __Pyx_ImportType("numpy", "flatiter", sizeof(PyArrayIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_flatiter)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 165; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_ptype_5numpy_broadcast = __Pyx_ImportType("numpy", "broadcast", sizeof(PyArrayMultiIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_broadcast)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 169; __pyx_clineno = __LINE__; goto __pyx_L1_error;} @@ -4527,48 +17440,72 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void) * # Copyright James Hensman and Alan Saul 2015 * * import numpy as np # <<<<<<<<<<<<<< + * from cython.parallel import prange, parallel * cimport numpy as np - * */ __pyx_t_1 = __Pyx_Import(__pyx_n_s_numpy, 0, -1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); if (PyDict_SetItem(__pyx_d, __pyx_n_s_np, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "GPy/util/choleskies_cython.pyx":10 + /* "GPy/util/choleskies_cython.pyx":11 * cimport numpy as np * * def flat_to_triang(np.ndarray[double, ndim=2] flat, int M): # <<<<<<<<<<<<<< * """take a matrix N x D and return a D X M x M array where * */ - __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_17choleskies_cython_1flat_to_triang, NULL, __pyx_n_s_GPy_util_choleskies_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 10; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_17choleskies_cython_1flat_to_triang, NULL, __pyx_n_s_GPy_util_choleskies_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 11; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_d, __pyx_n_s_flat_to_triang, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 10; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_d, __pyx_n_s_flat_to_triang, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 11; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "GPy/util/choleskies_cython.pyx":30 + /* "GPy/util/choleskies_cython.pyx":31 * return ret * * def triang_to_flat(np.ndarray[double, ndim=3] L): # <<<<<<<<<<<<<< * cdef int D = L.shape[0] * cdef int M = L.shape[1] */ - __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_17choleskies_cython_3triang_to_flat, NULL, __pyx_n_s_GPy_util_choleskies_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_17choleskies_cython_3triang_to_flat, NULL, __pyx_n_s_GPy_util_choleskies_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 31; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_d, __pyx_n_s_triang_to_flat, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 30; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_d, __pyx_n_s_triang_to_flat, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 31; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "GPy/util/choleskies_cython.pyx":46 + /* "GPy/util/choleskies_cython.pyx":47 * * * def backprop_gradient(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] L): # <<<<<<<<<<<<<< * cdef np.ndarray[double, ndim=2] dL_dK = np.tril(dL).copy() * cdef int N = L.shape[0] */ - __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_17choleskies_cython_5backprop_gradient, NULL, __pyx_n_s_GPy_util_choleskies_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_17choleskies_cython_5backprop_gradient, NULL, __pyx_n_s_GPy_util_choleskies_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_d, __pyx_n_s_backprop_gradient, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_d, __pyx_n_s_backprop_gradient, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; + + /* "GPy/util/choleskies_cython.pyx":62 + * return dL_dK + * + * def backprop_gradient_par(double[:,:] dL, double[:,:] L): # <<<<<<<<<<<<<< + * cdef double[:,:] dL_dK = np.tril(dL).copy() + * cdef int N = L.shape[0] + */ + __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_17choleskies_cython_7backprop_gradient_par, NULL, __pyx_n_s_GPy_util_choleskies_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 62; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + if (PyDict_SetItem(__pyx_d, __pyx_n_s_backprop_gradient_par, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 62; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; + + /* "GPy/util/choleskies_cython.pyx":82 + * void chol_backprop(int N, double* dL, double* L) + * + * def backprop_gradient_par_c(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] L): # <<<<<<<<<<<<<< + * cdef np.ndarray[double, ndim=2] dL_dK = np.tril(dL) # makes a copy, c-contig + * cdef int N = L.shape[0] + */ + __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_17choleskies_cython_9backprop_gradient_par_c, NULL, __pyx_n_s_GPy_util_choleskies_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 82; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + if (PyDict_SetItem(__pyx_d, __pyx_n_s_backprop_gradient_par_c, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 82; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "GPy/util/choleskies_cython.pyx":1 @@ -4581,12 +17518,121 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void) if (PyDict_SetItem(__pyx_d, __pyx_n_s_test, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":976 - * arr.base = baseptr + /* "View.MemoryView":203 + * info.obj = self * - * cdef inline object get_array_base(ndarray arr): # <<<<<<<<<<<<<< - * if arr.base is NULL: - * return None + * __pyx_getbuffer = capsule( &__pyx_array_getbuffer, "getbuffer(obj, view, flags)") # <<<<<<<<<<<<<< + * + * def __dealloc__(array self): + */ + __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_array_getbuffer)), __pyx_k_getbuffer_obj_view_flags); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 203; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + if (PyDict_SetItem(__pyx_array_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 203; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; + PyType_Modified(__pyx_array_type); + + /* "View.MemoryView":276 + * return self.name + * + * cdef generic = Enum("") # <<<<<<<<<<<<<< + * cdef strided = Enum("") # default + * cdef indirect = Enum("") + */ + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__28, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + __Pyx_XGOTREF(generic); + __Pyx_DECREF_SET(generic, __pyx_t_1); + __Pyx_GIVEREF(__pyx_t_1); + __pyx_t_1 = 0; + + /* "View.MemoryView":277 + * + * cdef generic = Enum("") + * cdef strided = Enum("") # default # <<<<<<<<<<<<<< + * cdef indirect = Enum("") + * + */ + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__29, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 277; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + __Pyx_XGOTREF(strided); + __Pyx_DECREF_SET(strided, __pyx_t_1); + __Pyx_GIVEREF(__pyx_t_1); + __pyx_t_1 = 0; + + /* "View.MemoryView":278 + * cdef generic = Enum("") + * cdef strided = Enum("") # default + * cdef indirect = Enum("") # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__30, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + __Pyx_XGOTREF(indirect); + __Pyx_DECREF_SET(indirect, __pyx_t_1); + __Pyx_GIVEREF(__pyx_t_1); + __pyx_t_1 = 0; + + /* "View.MemoryView":281 + * + * + * cdef contiguous = Enum("") # <<<<<<<<<<<<<< + * cdef indirect_contiguous = Enum("") + * + */ + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__31, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 281; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + __Pyx_XGOTREF(contiguous); + __Pyx_DECREF_SET(contiguous, __pyx_t_1); + __Pyx_GIVEREF(__pyx_t_1); + __pyx_t_1 = 0; + + /* "View.MemoryView":282 + * + * cdef contiguous = Enum("") + * cdef indirect_contiguous = Enum("") # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__32, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + __Pyx_XGOTREF(indirect_contiguous); + __Pyx_DECREF_SET(indirect_contiguous, __pyx_t_1); + __Pyx_GIVEREF(__pyx_t_1); + __pyx_t_1 = 0; + + /* "View.MemoryView":496 + * info.obj = self + * + * __pyx_getbuffer = capsule( &__pyx_memoryview_getbuffer, "getbuffer(obj, view, flags)") # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), __pyx_k_getbuffer_obj_view_flags); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 496; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + if (PyDict_SetItem(__pyx_memoryview_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 496; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; + PyType_Modified(__pyx_memoryview_type); + + /* "View.MemoryView":953 + * return self.from_object + * + * __pyx_getbuffer = capsule( &__pyx_memoryview_getbuffer, "getbuffer(obj, view, flags)") # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), __pyx_k_getbuffer_obj_view_flags); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 953; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + if (PyDict_SetItem(__pyx_memoryviewslice_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 953; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; + PyType_Modified(__pyx_memoryviewslice_type); + + /* "View.MemoryView":1361 + * + * @cname('__pyx_memoryview__slice_assign_scalar') + * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< + * Py_ssize_t *strides, int ndim, + * size_t itemsize, void *item) nogil: */ /*--- Wrapped vars code ---*/ @@ -5506,6 +18552,141 @@ static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) { } #endif +static int +__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, + int ndim, + __Pyx_memviewslice *memviewslice, + int memview_is_new_reference) +{ + __Pyx_RefNannyDeclarations + int i, retval=-1; + Py_buffer *buf = &memview->view; + __Pyx_RefNannySetupContext("init_memviewslice", 0); + if (!buf) { + PyErr_SetString(PyExc_ValueError, + "buf is NULL."); + goto fail; + } else if (memviewslice->memview || memviewslice->data) { + PyErr_SetString(PyExc_ValueError, + "memviewslice is already initialized!"); + goto fail; + } + if (buf->strides) { + for (i = 0; i < ndim; i++) { + memviewslice->strides[i] = buf->strides[i]; + } + } else { + Py_ssize_t stride = buf->itemsize; + for (i = ndim - 1; i >= 0; i--) { + memviewslice->strides[i] = stride; + stride *= buf->shape[i]; + } + } + for (i = 0; i < ndim; i++) { + memviewslice->shape[i] = buf->shape[i]; + if (buf->suboffsets) { + memviewslice->suboffsets[i] = buf->suboffsets[i]; + } else { + memviewslice->suboffsets[i] = -1; + } + } + memviewslice->memview = memview; + memviewslice->data = (char *)buf->buf; + if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) { + Py_INCREF(memview); + } + retval = 0; + goto no_fail; +fail: + memviewslice->memview = 0; + memviewslice->data = 0; + retval = -1; +no_fail: + __Pyx_RefNannyFinishContext(); + return retval; +} +static CYTHON_INLINE void __pyx_fatalerror(const char *fmt, ...) { + va_list vargs; + char msg[200]; + va_start(vargs, fmt); +#ifdef HAVE_STDARG_PROTOTYPES + va_start(vargs, fmt); +#else + va_start(vargs); +#endif + vsnprintf(msg, 200, fmt, vargs); + Py_FatalError(msg); + va_end(vargs); +} +static CYTHON_INLINE int +__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count, + PyThread_type_lock lock) +{ + int result; + PyThread_acquire_lock(lock, 1); + result = (*acquisition_count)++; + PyThread_release_lock(lock); + return result; +} +static CYTHON_INLINE int +__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count, + PyThread_type_lock lock) +{ + int result; + PyThread_acquire_lock(lock, 1); + result = (*acquisition_count)--; + PyThread_release_lock(lock); + return result; +} +static CYTHON_INLINE void +__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) +{ + int first_time; + struct __pyx_memoryview_obj *memview = memslice->memview; + if (!memview || (PyObject *) memview == Py_None) + return; + if (__pyx_get_slice_count(memview) < 0) + __pyx_fatalerror("Acquisition count is %d (line %d)", + __pyx_get_slice_count(memview), lineno); + first_time = __pyx_add_acquisition_count(memview) == 0; + if (first_time) { + if (have_gil) { + Py_INCREF((PyObject *) memview); + } else { + PyGILState_STATE _gilstate = PyGILState_Ensure(); + Py_INCREF((PyObject *) memview); + PyGILState_Release(_gilstate); + } + } +} +static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, + int have_gil, int lineno) { + int last_time; + struct __pyx_memoryview_obj *memview = memslice->memview; + if (!memview ) { + return; + } else if ((PyObject *) memview == Py_None) { + memslice->memview = NULL; + return; + } + if (__pyx_get_slice_count(memview) <= 0) + __pyx_fatalerror("Acquisition count is %d (line %d)", + __pyx_get_slice_count(memview), lineno); + last_time = __pyx_sub_acquisition_count(memview) == 1; + memslice->data = NULL; + if (last_time) { + if (have_gil) { + Py_CLEAR(memslice->memview); + } else { + PyGILState_STATE _gilstate = PyGILState_Ensure(); + Py_CLEAR(memslice->memview); + PyGILState_Release(_gilstate); + } + } else { + memslice->memview = NULL; + } +} + #if PY_MAJOR_VERSION < 3 static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, CYTHON_UNUSED PyObject *cause) { @@ -5670,6 +18851,404 @@ static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); } +static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) { +#if CYTHON_COMPILING_IN_PYPY + return PyObject_RichCompareBool(s1, s2, equals); +#else + if (s1 == s2) { + return (equals == Py_EQ); + } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) { + const char *ps1, *ps2; + Py_ssize_t length = PyBytes_GET_SIZE(s1); + if (length != PyBytes_GET_SIZE(s2)) + return (equals == Py_NE); + ps1 = PyBytes_AS_STRING(s1); + ps2 = PyBytes_AS_STRING(s2); + if (ps1[0] != ps2[0]) { + return (equals == Py_NE); + } else if (length == 1) { + return (equals == Py_EQ); + } else { + int result = memcmp(ps1, ps2, (size_t)length); + return (equals == Py_EQ) ? (result == 0) : (result != 0); + } + } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) { + return (equals == Py_NE); + } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) { + return (equals == Py_NE); + } else { + int result; + PyObject* py_result = PyObject_RichCompare(s1, s2, equals); + if (!py_result) + return -1; + result = __Pyx_PyObject_IsTrue(py_result); + Py_DECREF(py_result); + return result; + } +#endif +} + +static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) { +#if CYTHON_COMPILING_IN_PYPY + return PyObject_RichCompareBool(s1, s2, equals); +#else +#if PY_MAJOR_VERSION < 3 + PyObject* owned_ref = NULL; +#endif + int s1_is_unicode, s2_is_unicode; + if (s1 == s2) { + goto return_eq; + } + s1_is_unicode = PyUnicode_CheckExact(s1); + s2_is_unicode = PyUnicode_CheckExact(s2); +#if PY_MAJOR_VERSION < 3 + if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) { + owned_ref = PyUnicode_FromObject(s2); + if (unlikely(!owned_ref)) + return -1; + s2 = owned_ref; + s2_is_unicode = 1; + } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) { + owned_ref = PyUnicode_FromObject(s1); + if (unlikely(!owned_ref)) + return -1; + s1 = owned_ref; + s1_is_unicode = 1; + } else if (((!s2_is_unicode) & (!s1_is_unicode))) { + return __Pyx_PyBytes_Equals(s1, s2, equals); + } +#endif + if (s1_is_unicode & s2_is_unicode) { + Py_ssize_t length; + int kind; + void *data1, *data2; + if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0)) + return -1; + length = __Pyx_PyUnicode_GET_LENGTH(s1); + if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) { + goto return_ne; + } + kind = __Pyx_PyUnicode_KIND(s1); + if (kind != __Pyx_PyUnicode_KIND(s2)) { + goto return_ne; + } + data1 = __Pyx_PyUnicode_DATA(s1); + data2 = __Pyx_PyUnicode_DATA(s2); + if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) { + goto return_ne; + } else if (length == 1) { + goto return_eq; + } else { + int result = memcmp(data1, data2, (size_t)(length * kind)); + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_EQ) ? (result == 0) : (result != 0); + } + } else if ((s1 == Py_None) & s2_is_unicode) { + goto return_ne; + } else if ((s2 == Py_None) & s1_is_unicode) { + goto return_ne; + } else { + int result; + PyObject* py_result = PyObject_RichCompare(s1, s2, equals); + if (!py_result) + return -1; + result = __Pyx_PyObject_IsTrue(py_result); + Py_DECREF(py_result); + return result; + } +return_eq: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_EQ); +return_ne: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_NE); +#endif +} + +static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t a, Py_ssize_t b) { + Py_ssize_t q = a / b; + Py_ssize_t r = a - q*b; + q -= ((r != 0) & ((r ^ b) < 0)); + return q; +} + +static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) { +#if CYTHON_COMPILING_IN_CPYTHON +#if PY_MAJOR_VERSION >= 3 + if (likely(PyUnicode_Check(n))) +#else + if (likely(PyString_Check(n))) +#endif + return __Pyx_PyObject_GetAttrStr(o, n); +#endif + return PyObject_GetAttr(o, n); +} + +static CYTHON_INLINE PyObject* __Pyx_decode_c_string( + const char* cstring, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) { + Py_ssize_t length; + if (unlikely((start < 0) | (stop < 0))) { + length = strlen(cstring); + if (start < 0) { + start += length; + if (start < 0) + start = 0; + } + if (stop < 0) + stop += length; + } + length = stop - start; + if (unlikely(length <= 0)) + return PyUnicode_FromUnicode(NULL, 0); + cstring += start; + if (decode_func) { + return decode_func(cstring, length, errors); + } else { + return PyUnicode_Decode(cstring, length, encoding, errors); + } +} + +static CYTHON_INLINE void __Pyx_ExceptionSave(PyObject **type, PyObject **value, PyObject **tb) { +#if CYTHON_COMPILING_IN_CPYTHON + PyThreadState *tstate = PyThreadState_GET(); + *type = tstate->exc_type; + *value = tstate->exc_value; + *tb = tstate->exc_traceback; + Py_XINCREF(*type); + Py_XINCREF(*value); + Py_XINCREF(*tb); +#else + PyErr_GetExcInfo(type, value, tb); +#endif +} +static void __Pyx_ExceptionReset(PyObject *type, PyObject *value, PyObject *tb) { +#if CYTHON_COMPILING_IN_CPYTHON + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyThreadState *tstate = PyThreadState_GET(); + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = type; + tstate->exc_value = value; + tstate->exc_traceback = tb; + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(type, value, tb); +#endif +} + +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) { + PyObject *local_type, *local_value, *local_tb; +#if CYTHON_COMPILING_IN_CPYTHON + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyThreadState *tstate = PyThreadState_GET(); + local_type = tstate->curexc_type; + local_value = tstate->curexc_value; + local_tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +#else + PyErr_Fetch(&local_type, &local_value, &local_tb); +#endif + PyErr_NormalizeException(&local_type, &local_value, &local_tb); +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(tstate->curexc_type)) +#else + if (unlikely(PyErr_Occurred())) +#endif + goto bad; + #if PY_MAJOR_VERSION >= 3 + if (local_tb) { + if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) + goto bad; + } + #endif + Py_XINCREF(local_tb); + Py_XINCREF(local_type); + Py_XINCREF(local_value); + *type = local_type; + *value = local_value; + *tb = local_tb; +#if CYTHON_COMPILING_IN_CPYTHON + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = local_type; + tstate->exc_value = local_value; + tstate->exc_traceback = local_tb; + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(local_type, local_value, local_tb); +#endif + return 0; +bad: + *type = 0; + *value = 0; + *tb = 0; + Py_XDECREF(local_type); + Py_XDECREF(local_value); + Py_XDECREF(local_tb); + return -1; +} + +static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; +#if CYTHON_COMPILING_IN_CPYTHON + PyThreadState *tstate = PyThreadState_GET(); + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = *type; + tstate->exc_value = *value; + tstate->exc_traceback = *tb; +#else + PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb); + PyErr_SetExcInfo(*type, *value, *tb); +#endif + *type = tmp_type; + *value = tmp_value; + *tb = tmp_tb; +} + +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { + PyObject *r; + if (!j) return NULL; + r = PyObject_GetItem(o, j); + Py_DECREF(j); + return r; +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck) { +#if CYTHON_COMPILING_IN_CPYTHON + if (wraparound & unlikely(i < 0)) i += PyList_GET_SIZE(o); + if ((!boundscheck) || likely((0 <= i) & (i < PyList_GET_SIZE(o)))) { + PyObject *r = PyList_GET_ITEM(o, i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck) { +#if CYTHON_COMPILING_IN_CPYTHON + if (wraparound & unlikely(i < 0)) i += PyTuple_GET_SIZE(o); + if ((!boundscheck) || likely((0 <= i) & (i < PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, + int is_list, int wraparound, int boundscheck) { +#if CYTHON_COMPILING_IN_CPYTHON + if (is_list || PyList_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); + if ((!boundscheck) || (likely((n >= 0) & (n < PyList_GET_SIZE(o))))) { + PyObject *r = PyList_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } + else if (PyTuple_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); + if ((!boundscheck) || likely((n >= 0) & (n < PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } else { + PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; + if (likely(m && m->sq_item)) { + if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { + Py_ssize_t l = m->sq_length(o); + if (likely(l >= 0)) { + i += l; + } else { + if (PyErr_ExceptionMatches(PyExc_OverflowError)) + PyErr_Clear(); + else + return NULL; + } + } + return m->sq_item(o, i); + } + } +#else + if (is_list || PySequence_Check(o)) { + return PySequence_GetItem(o, i); + } +#endif + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +} + +static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) { + PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname); +} + +static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno, + CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename, + int full_traceback) { + PyObject *old_exc, *old_val, *old_tb; + PyObject *ctx; + __Pyx_ErrFetch(&old_exc, &old_val, &old_tb); + if (full_traceback) { + Py_XINCREF(old_exc); + Py_XINCREF(old_val); + Py_XINCREF(old_tb); + __Pyx_ErrRestore(old_exc, old_val, old_tb); + PyErr_PrintEx(1); + } + #if PY_MAJOR_VERSION < 3 + ctx = PyString_FromString(name); + #else + ctx = PyUnicode_FromString(name); + #endif + __Pyx_ErrRestore(old_exc, old_val, old_tb); + if (!ctx) { + PyErr_WriteUnraisable(Py_None); + } else { + PyErr_WriteUnraisable(ctx); + Py_DECREF(ctx); + } +} + +static int __Pyx_SetVtable(PyObject *dict, void *vtable) { +#if PY_VERSION_HEX >= 0x02070000 + PyObject *ob = PyCapsule_New(vtable, 0, 0); +#else + PyObject *ob = PyCObject_FromVoidPtr(vtable, 0); +#endif + if (!ob) + goto bad; + if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0) + goto bad; + Py_DECREF(ob); + return 0; +bad: + Py_XDECREF(ob); + return -1; +} + static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { int start = 0, mid = 0, end = count - 1; if (end >= 0 && code_line > entries[end].code_line) { @@ -5833,6 +19412,8 @@ bad: static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) return __pyx_pw_5numpy_7ndarray_1__getbuffer__(obj, view, flags); + if (PyObject_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags); + if (PyObject_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags); PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); return -1; } @@ -6039,6 +19620,249 @@ raise_neg_overflow: return (int) -1; } +static int +__pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b) +{ + int i; + if (!a || !b) + return 0; + if (a == b) + return 1; + if (a->size != b->size || a->typegroup != b->typegroup || + a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) { + if (a->typegroup == 'H' || b->typegroup == 'H') { + return a->size == b->size; + } else { + return 0; + } + } + if (a->ndim) { + for (i = 0; i < a->ndim; i++) + if (a->arraysize[i] != b->arraysize[i]) + return 0; + } + if (a->typegroup == 'S') { + if (a->flags != b->flags) + return 0; + if (a->fields || b->fields) { + if (!(a->fields && b->fields)) + return 0; + for (i = 0; a->fields[i].type && b->fields[i].type; i++) { + __Pyx_StructField *field_a = a->fields + i; + __Pyx_StructField *field_b = b->fields + i; + if (field_a->offset != field_b->offset || + !__pyx_typeinfo_cmp(field_a->type, field_b->type)) + return 0; + } + return !a->fields[i].type && !b->fields[i].type; + } + } + return 1; +} + +static int +__pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec) +{ + if (buf->shape[dim] <= 1) + return 1; + if (buf->strides) { + if (spec & __Pyx_MEMVIEW_CONTIG) { + if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) { + if (buf->strides[dim] != sizeof(void *)) { + PyErr_Format(PyExc_ValueError, + "Buffer is not indirectly contiguous " + "in dimension %d.", dim); + goto fail; + } + } else if (buf->strides[dim] != buf->itemsize) { + PyErr_SetString(PyExc_ValueError, + "Buffer and memoryview are not contiguous " + "in the same dimension."); + goto fail; + } + } + if (spec & __Pyx_MEMVIEW_FOLLOW) { + Py_ssize_t stride = buf->strides[dim]; + if (stride < 0) + stride = -stride; + if (stride < buf->itemsize) { + PyErr_SetString(PyExc_ValueError, + "Buffer and memoryview are not contiguous " + "in the same dimension."); + goto fail; + } + } + } else { + if (spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1) { + PyErr_Format(PyExc_ValueError, + "C-contiguous buffer is not contiguous in " + "dimension %d", dim); + goto fail; + } else if (spec & (__Pyx_MEMVIEW_PTR)) { + PyErr_Format(PyExc_ValueError, + "C-contiguous buffer is not indirect in " + "dimension %d", dim); + goto fail; + } else if (buf->suboffsets) { + PyErr_SetString(PyExc_ValueError, + "Buffer exposes suboffsets but no strides"); + goto fail; + } + } + return 1; +fail: + return 0; +} +static int +__pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec) +{ + if (spec & __Pyx_MEMVIEW_DIRECT) { + if (buf->suboffsets && buf->suboffsets[dim] >= 0) { + PyErr_Format(PyExc_ValueError, + "Buffer not compatible with direct access " + "in dimension %d.", dim); + goto fail; + } + } + if (spec & __Pyx_MEMVIEW_PTR) { + if (!buf->suboffsets || (buf->suboffsets && buf->suboffsets[dim] < 0)) { + PyErr_Format(PyExc_ValueError, + "Buffer is not indirectly accessible " + "in dimension %d.", dim); + goto fail; + } + } + return 1; +fail: + return 0; +} +static int +__pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag) +{ + int i; + if (c_or_f_flag & __Pyx_IS_F_CONTIG) { + Py_ssize_t stride = 1; + for (i = 0; i < ndim; i++) { + if (stride * buf->itemsize != buf->strides[i] && + buf->shape[i] > 1) + { + PyErr_SetString(PyExc_ValueError, + "Buffer not fortran contiguous."); + goto fail; + } + stride = stride * buf->shape[i]; + } + } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) { + Py_ssize_t stride = 1; + for (i = ndim - 1; i >- 1; i--) { + if (stride * buf->itemsize != buf->strides[i] && + buf->shape[i] > 1) { + PyErr_SetString(PyExc_ValueError, + "Buffer not C contiguous."); + goto fail; + } + stride = stride * buf->shape[i]; + } + } + return 1; +fail: + return 0; +} +static int __Pyx_ValidateAndInit_memviewslice( + int *axes_specs, + int c_or_f_flag, + int buf_flags, + int ndim, + __Pyx_TypeInfo *dtype, + __Pyx_BufFmt_StackElem stack[], + __Pyx_memviewslice *memviewslice, + PyObject *original_obj) +{ + struct __pyx_memoryview_obj *memview, *new_memview; + __Pyx_RefNannyDeclarations + Py_buffer *buf; + int i, spec = 0, retval = -1; + __Pyx_BufFmt_Context ctx; + int from_memoryview = __pyx_memoryview_check(original_obj); + __Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0); + if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *) + original_obj)->typeinfo)) { + memview = (struct __pyx_memoryview_obj *) original_obj; + new_memview = NULL; + } else { + memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( + original_obj, buf_flags, 0, dtype); + new_memview = memview; + if (unlikely(!memview)) + goto fail; + } + buf = &memview->view; + if (buf->ndim != ndim) { + PyErr_Format(PyExc_ValueError, + "Buffer has wrong number of dimensions (expected %d, got %d)", + ndim, buf->ndim); + goto fail; + } + if (new_memview) { + __Pyx_BufFmt_Init(&ctx, stack, dtype); + if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; + } + if ((unsigned) buf->itemsize != dtype->size) { + PyErr_Format(PyExc_ValueError, + "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) " + "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)", + buf->itemsize, + (buf->itemsize > 1) ? "s" : "", + dtype->name, + dtype->size, + (dtype->size > 1) ? "s" : ""); + goto fail; + } + for (i = 0; i < ndim; i++) { + spec = axes_specs[i]; + if (!__pyx_check_strides(buf, i, ndim, spec)) + goto fail; + if (!__pyx_check_suboffsets(buf, i, ndim, spec)) + goto fail; + } + if (buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag)) + goto fail; + if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice, + new_memview != NULL) == -1)) { + goto fail; + } + retval = 0; + goto no_fail; +fail: + Py_XDECREF(new_memview); + retval = -1; +no_fail: + __Pyx_RefNannyFinishContext(); + return retval; +} + +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_double(PyObject *obj) { + __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; + __Pyx_BufFmt_StackElem stack[1]; + int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; + int retcode; + if (obj == Py_None) { + result.memview = (struct __pyx_memoryview_obj *) Py_None; + return result; + } + retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, + PyBUF_RECORDS, 2, + &__Pyx_TypeInfo_double, stack, + &result, obj); + if (unlikely(retcode == -1)) + goto __pyx_fail; + return result; +__pyx_fail: + result.memview = NULL; + result.data = NULL; + return result; +} + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { const int neg_one = (int) -1, const_zero = 0; const int is_unsigned = neg_one > const_zero; @@ -6091,6 +19915,17 @@ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { } } +static PyObject *__pyx_memview_get_double(const char *itemp) { + return (PyObject *) PyFloat_FromDouble(*(double *) itemp); +} +static int __pyx_memview_set_double(const char *itemp, PyObject *obj) { + double value = __pyx_PyFloat_AsDouble(obj); + if ((value == (double)-1) && PyErr_Occurred()) + return 0; + *(double *) itemp = value; + return 1; +} + #if CYTHON_CCOMPLEX #ifdef __cplusplus static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { @@ -6331,6 +20166,236 @@ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { #endif #endif +static int +__pyx_memviewslice_is_contig(const __Pyx_memviewslice *mvs, + char order, int ndim) +{ + int i, index, step, start; + Py_ssize_t itemsize = mvs->memview->view.itemsize; + if (order == 'F') { + step = 1; + start = 0; + } else { + step = -1; + start = ndim - 1; + } + for (i = 0; i < ndim; i++) { + index = start + step * i; + if (mvs->suboffsets[index] >= 0 || mvs->strides[index] != itemsize) + return 0; + itemsize *= mvs->shape[index]; + } + return 1; +} + +static void +__pyx_get_array_memory_extents(__Pyx_memviewslice *slice, + void **out_start, void **out_end, + int ndim, size_t itemsize) +{ + char *start, *end; + int i; + start = end = slice->data; + for (i = 0; i < ndim; i++) { + Py_ssize_t stride = slice->strides[i]; + Py_ssize_t extent = slice->shape[i]; + if (extent == 0) { + *out_start = *out_end = start; + return; + } else { + if (stride > 0) + end += stride * (extent - 1); + else + start += stride * (extent - 1); + } + } + *out_start = start; + *out_end = end + itemsize; +} +static int +__pyx_slices_overlap(__Pyx_memviewslice *slice1, + __Pyx_memviewslice *slice2, + int ndim, size_t itemsize) +{ + void *start1, *end1, *start2, *end2; + __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize); + __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize); + return (start1 < end2) && (start2 < end1); +} + +static __Pyx_memviewslice +__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, + const char *mode, int ndim, + size_t sizeof_dtype, int contig_flag, + int dtype_is_object) +{ + __Pyx_RefNannyDeclarations + int i; + __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } }; + struct __pyx_memoryview_obj *from_memview = from_mvs->memview; + Py_buffer *buf = &from_memview->view; + PyObject *shape_tuple = NULL; + PyObject *temp_int = NULL; + struct __pyx_array_obj *array_obj = NULL; + struct __pyx_memoryview_obj *memview_obj = NULL; + __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0); + for (i = 0; i < ndim; i++) { + if (from_mvs->suboffsets[i] >= 0) { + PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with " + "indirect dimensions (axis %d)", i); + goto fail; + } + } + shape_tuple = PyTuple_New(ndim); + if (unlikely(!shape_tuple)) { + goto fail; + } + __Pyx_GOTREF(shape_tuple); + for(i = 0; i < ndim; i++) { + temp_int = PyInt_FromSsize_t(from_mvs->shape[i]); + if(unlikely(!temp_int)) { + goto fail; + } else { + PyTuple_SET_ITEM(shape_tuple, i, temp_int); + temp_int = NULL; + } + } + array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL); + if (unlikely(!array_obj)) { + goto fail; + } + __Pyx_GOTREF(array_obj); + memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( + (PyObject *) array_obj, contig_flag, + dtype_is_object, + from_mvs->memview->typeinfo); + if (unlikely(!memview_obj)) + goto fail; + if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0)) + goto fail; + if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim, + dtype_is_object) < 0)) + goto fail; + goto no_fail; +fail: + __Pyx_XDECREF(new_mvs.memview); + new_mvs.memview = NULL; + new_mvs.data = NULL; +no_fail: + __Pyx_XDECREF(shape_tuple); + __Pyx_XDECREF(temp_int); + __Pyx_XDECREF(array_obj); + __Pyx_RefNannyFinishContext(); + return new_mvs; +} + +static CYTHON_INLINE PyObject * +__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig) +{ + PyObject *cobj; +#if PY_VERSION_HEX >= 0x02070000 + cobj = PyCapsule_New(p, sig, NULL); +#else + cobj = PyCObject_FromVoidPtr(p, NULL); +#endif + return cobj; +} + +static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) { + const char neg_one = (char) -1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(char) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (char) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 + #if CYTHON_USE_PYLONG_INTERNALS + switch (Py_SIZE(x)) { + case 0: return 0; + case 1: __PYX_VERIFY_RETURN_INT(char, digit, ((PyLongObject*)x)->ob_digit[0]); + } + #endif +#endif + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } + if (sizeof(char) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, PyLong_AsUnsignedLong(x)) + } else if (sizeof(char) <= sizeof(unsigned long long)) { + __PYX_VERIFY_RETURN_INT(char, unsigned long long, PyLong_AsUnsignedLongLong(x)) + } + } else { +#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3 + #if CYTHON_USE_PYLONG_INTERNALS + switch (Py_SIZE(x)) { + case 0: return 0; + case 1: __PYX_VERIFY_RETURN_INT(char, digit, +(((PyLongObject*)x)->ob_digit[0])); + case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]); + } + #endif +#endif + if (sizeof(char) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT(char, long, PyLong_AsLong(x)) + } else if (sizeof(char) <= sizeof(long long)) { + __PYX_VERIFY_RETURN_INT(char, long long, PyLong_AsLongLong(x)) + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + char val; + PyObject *v = __Pyx_PyNumber_Int(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (char) -1; + } + } else { + char val; + PyObject *tmp = __Pyx_PyNumber_Int(x); + if (!tmp) return (char) -1; + val = __Pyx_PyInt_As_char(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to char"); + return (char) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to char"); + return (char) -1; +} + static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { const long neg_one = (long) -1, const_zero = 0; const int is_unsigned = neg_one > const_zero; diff --git a/GPy/util/choleskies_cython.pyx b/GPy/util/choleskies_cython.pyx index 76b49b22..50fa6709 100644 --- a/GPy/util/choleskies_cython.pyx +++ b/GPy/util/choleskies_cython.pyx @@ -5,6 +5,7 @@ # Copyright James Hensman and Alan Saul 2015 import numpy as np +from cython.parallel import prange, parallel cimport numpy as np def flat_to_triang(np.ndarray[double, ndim=2] flat, int M): @@ -57,3 +58,30 @@ def backprop_gradient(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] dL_dK[k, k] -= L[j, k] * dL_dK[j, k] dL_dK[k, k] /= (2. * L[k, k]) return dL_dK + +def backprop_gradient_par(double[:,:] dL, double[:,:] L): + cdef double[:,:] dL_dK = np.tril(dL).copy() + cdef int N = L.shape[0] + cdef int k, j, i + for k in range(N - 1, -1, -1): + with nogil, parallel(): + for i in prange(k + 1, N): + for j in range(k+1, i+1): + dL_dK[i, k] -= dL_dK[i, j] * L[j, k] + for j in range(i, N): + dL_dK[i, k] -= dL_dK[j, i] * L[j, k] + for j in range(k + 1, N): + dL_dK[j, k] /= L[k, k] + dL_dK[k, k] -= L[j, k] * dL_dK[j, k] + dL_dK[k, k] /= (2. * L[k, k]) + return dL_dK + +cdef extern from "cholesky_backprop.h": + void chol_backprop(int N, double* dL, double* L) + +def backprop_gradient_par_c(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] L): + cdef np.ndarray[double, ndim=2] dL_dK = np.tril(dL) # makes a copy, c-contig + cdef int N = L.shape[0] + chol_backprop(N, dL_dK.data, L.data) + return dL_dK + diff --git a/GPy/util/cholesky_backprop.c b/GPy/util/cholesky_backprop.c new file mode 100644 index 00000000..e3919abb --- /dev/null +++ b/GPy/util/cholesky_backprop.c @@ -0,0 +1,22 @@ + +void chol_backprop(int N, double* dL, double* L){ + //at the input to this fn, dL is df_dL. after this fn is complet, dL is df_dK + int i,j,k; + for(k=N-1;k>(-1);k--){ + #pragma omp parallel for private(i,j) + for(i=k+1;i Date: Mon, 8 Jun 2015 21:09:45 +0100 Subject: [PATCH 34/41] fiddling with cholesky backprop --- GPy/util/choleskies.py | 2 +- GPy/util/choleskies_cython.c | 800 ++++++++++++++++++++++++++++++--- GPy/util/choleskies_cython.pyx | 28 +- GPy/util/cholesky_backprop.c | 40 +- GPy/util/cholesky_backprop.h | 1 + setup.py | 3 +- 6 files changed, 793 insertions(+), 81 deletions(-) diff --git a/GPy/util/choleskies.py b/GPy/util/choleskies.py index 7afc3098..a12631aa 100644 --- a/GPy/util/choleskies.py +++ b/GPy/util/choleskies.py @@ -100,7 +100,7 @@ def indexes_to_fix_for_low_rank(rank, size): if config.getboolean('cython', 'working'): triang_to_flat = _triang_to_flat_cython flat_to_triang = _flat_to_triang_cython - backprop_gradient = choleskies_cython.backprop_gradient + backprop_gradient = choleskies_cython.backprop_gradient_par_c else: backprop_gradient = _backprop_gradient_pure triang_to_flat = _triang_to_flat_pure diff --git a/GPy/util/choleskies_cython.c b/GPy/util/choleskies_cython.c index c5d1867e..db7d1aed 100644 --- a/GPy/util/choleskies_cython.c +++ b/GPy/util/choleskies_cython.c @@ -1470,6 +1470,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_4backprop_gradient(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_dL, PyArrayObject *__pyx_v_L); /* proto */ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_dL, __Pyx_memviewslice __pyx_v_L); /* proto */ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_8backprop_gradient_par_c(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_dL, PyArrayObject *__pyx_v_L); /* proto */ +static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_10backprop_gradient_par2(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_dL, __Pyx_memviewslice __pyx_v_L); /* proto */ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */ static int __pyx_array_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ @@ -1533,9 +1534,12 @@ static char __pyx_k_Zd[] = "Zd"; static char __pyx_k_Zf[] = "Zf"; static char __pyx_k_Zg[] = "Zg"; static char __pyx_k_dL[] = "dL"; +static char __pyx_k_iN[] = "iN"; static char __pyx_k_id[] = "id"; +static char __pyx_k_kN[] = "kN"; static char __pyx_k_mm[] = "mm"; static char __pyx_k_np[] = "np"; +static char __pyx_k_dot[] = "dot"; static char __pyx_k_obj[] = "obj"; static char __pyx_k_ret[] = "ret"; static char __pyx_k_base[] = "base"; @@ -1568,6 +1572,7 @@ static char __pyx_k_name_2[] = "__name__"; static char __pyx_k_struct[] = "struct"; static char __pyx_k_unpack[] = "unpack"; static char __pyx_k_xrange[] = "xrange"; +static char __pyx_k_asarray[] = "asarray"; static char __pyx_k_fortran[] = "fortran"; static char __pyx_k_memview[] = "memview"; static char __pyx_k_Ellipsis[] = "Ellipsis"; @@ -1590,6 +1595,7 @@ static char __pyx_k_strided_and_indirect[] = ""; static char __pyx_k_backprop_gradient_par[] = "backprop_gradient_par"; static char __pyx_k_contiguous_and_direct[] = ""; static char __pyx_k_MemoryView_of_r_object[] = ""; +static char __pyx_k_backprop_gradient_par2[] = "backprop_gradient_par2"; static char __pyx_k_MemoryView_of_r_at_0x_x[] = ""; static char __pyx_k_backprop_gradient_par_c[] = "backprop_gradient_par_c"; static char __pyx_k_contiguous_and_indirect[] = ""; @@ -1604,7 +1610,7 @@ static char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.ar static char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous"; static char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; static char __pyx_k_strided_and_direct_or_indirect[] = ""; -static char __pyx_k_home_james_work_GPy_GPy_util_ch[] = "/home/james/work/GPy/GPy/util/choleskies_cython.pyx"; +static char __pyx_k_Users_james_work_GPy_GPy_util_c[] = "/Users/james/work/GPy/GPy/util/choleskies_cython.pyx"; static char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)"; static char __pyx_k_All_dimensions_preceding_dimensi[] = "All dimensions preceding dimension %d must be indexed and not sliced"; static char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; @@ -1646,10 +1652,13 @@ static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a; static PyObject *__pyx_n_s_RuntimeError; static PyObject *__pyx_n_s_TypeError; static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object; +static PyObject *__pyx_kp_s_Users_james_work_GPy_GPy_util_c; static PyObject *__pyx_n_s_ValueError; static PyObject *__pyx_n_s_allocate_buffer; +static PyObject *__pyx_n_s_asarray; static PyObject *__pyx_n_s_backprop_gradient; static PyObject *__pyx_n_s_backprop_gradient_par; +static PyObject *__pyx_n_s_backprop_gradient_par2; static PyObject *__pyx_n_s_backprop_gradient_par_c; static PyObject *__pyx_n_s_base; static PyObject *__pyx_n_s_c; @@ -1662,6 +1671,7 @@ static PyObject *__pyx_n_s_count; static PyObject *__pyx_n_s_d; static PyObject *__pyx_n_s_dL; static PyObject *__pyx_n_s_dL_dK; +static PyObject *__pyx_n_s_dot; static PyObject *__pyx_n_s_dtype_is_object; static PyObject *__pyx_n_s_empty; static PyObject *__pyx_n_s_enumerate; @@ -1673,14 +1683,15 @@ static PyObject *__pyx_n_s_format; static PyObject *__pyx_n_s_fortran; static PyObject *__pyx_n_u_fortran; static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi; -static PyObject *__pyx_kp_s_home_james_work_GPy_GPy_util_ch; static PyObject *__pyx_n_s_i; +static PyObject *__pyx_n_s_iN; static PyObject *__pyx_n_s_id; static PyObject *__pyx_n_s_import; static PyObject *__pyx_n_s_itemsize; static PyObject *__pyx_kp_s_itemsize_0_for_cython_array; static PyObject *__pyx_n_s_j; static PyObject *__pyx_n_s_k; +static PyObject *__pyx_n_s_kN; static PyObject *__pyx_n_s_m; static PyObject *__pyx_n_s_main; static PyObject *__pyx_n_s_memview; @@ -1743,15 +1754,17 @@ static PyObject *__pyx_tuple__22; static PyObject *__pyx_tuple__24; static PyObject *__pyx_tuple__26; static PyObject *__pyx_tuple__28; -static PyObject *__pyx_tuple__29; static PyObject *__pyx_tuple__30; static PyObject *__pyx_tuple__31; static PyObject *__pyx_tuple__32; +static PyObject *__pyx_tuple__33; +static PyObject *__pyx_tuple__34; static PyObject *__pyx_codeobj__19; static PyObject *__pyx_codeobj__21; static PyObject *__pyx_codeobj__23; static PyObject *__pyx_codeobj__25; static PyObject *__pyx_codeobj__27; +static PyObject *__pyx_codeobj__29; /* "GPy/util/choleskies_cython.pyx":11 * cimport numpy as np @@ -3043,7 +3056,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par( #define unlikely(x) (x) #endif #ifdef _OPENMP - #pragma omp parallel private(__pyx_t_26, __pyx_t_14, __pyx_t_20, __pyx_t_27, __pyx_t_22, __pyx_t_10, __pyx_t_11, __pyx_t_23, __pyx_t_9, __pyx_t_25, __pyx_t_16, __pyx_t_21, __pyx_t_17, __pyx_t_19, __pyx_t_15, __pyx_t_13, __pyx_t_12, __pyx_t_18, __pyx_t_24) + #pragma omp parallel private(__pyx_t_9, __pyx_t_25, __pyx_t_20, __pyx_t_16, __pyx_t_21, __pyx_t_17, __pyx_t_14, __pyx_t_19, __pyx_t_22, __pyx_t_10, __pyx_t_11, __pyx_t_23, __pyx_t_13, __pyx_t_12, __pyx_t_18, __pyx_t_24, __pyx_t_26, __pyx_t_15, __pyx_t_27) #endif /* _OPENMP */ { @@ -3240,7 +3253,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par( * dL_dK[k, k] /= (2. * L[k, k]) * return dL_dK # <<<<<<<<<<<<<< * - * cdef extern from "cholesky_backprop.h": + * #here's a pure C version... */ __Pyx_XDECREF(__pyx_r); __pyx_t_1 = __pyx_memoryview_fromslice(__pyx_v_dL_dK, 2, (PyObject *(*)(char *)) __pyx_memview_get_double, (int (*)(char *, PyObject *)) __pyx_memview_set_double, 0);; if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} @@ -3277,7 +3290,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par( return __pyx_r; } -/* "GPy/util/choleskies_cython.pyx":82 +/* "GPy/util/choleskies_cython.pyx":83 * void chol_backprop(int N, double* dL, double* L) * * def backprop_gradient_par_c(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] L): # <<<<<<<<<<<<<< @@ -3317,11 +3330,11 @@ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_9backprop_gradient_par_ case 1: if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_L)) != 0)) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("backprop_gradient_par_c", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 82; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("backprop_gradient_par_c", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "backprop_gradient_par_c") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 82; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "backprop_gradient_par_c") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } else if (PyTuple_GET_SIZE(__pyx_args) != 2) { goto __pyx_L5_argtuple_error; @@ -3334,14 +3347,14 @@ static PyObject *__pyx_pw_3GPy_4util_17choleskies_cython_9backprop_gradient_par_ } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("backprop_gradient_par_c", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 82; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("backprop_gradient_par_c", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("GPy.util.choleskies_cython.backprop_gradient_par_c", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return NULL; __pyx_L4_argument_unpacking_done:; - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_dL), __pyx_ptype_5numpy_ndarray, 1, "dL", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 82; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_L), __pyx_ptype_5numpy_ndarray, 1, "L", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 82; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_dL), __pyx_ptype_5numpy_ndarray, 1, "dL", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_L), __pyx_ptype_5numpy_ndarray, 1, "L", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_r = __pyx_pf_3GPy_4util_17choleskies_cython_8backprop_gradient_par_c(__pyx_self, __pyx_v_dL, __pyx_v_L); /* function exit code */ @@ -3387,25 +3400,25 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_8backprop_gradient_par_ __pyx_pybuffernd_L.rcbuffer = &__pyx_pybuffer_L; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_dL.rcbuffer->pybuffer, (PyObject*)__pyx_v_dL, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 82; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_dL.rcbuffer->pybuffer, (PyObject*)__pyx_v_dL, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd_dL.diminfo[0].strides = __pyx_pybuffernd_dL.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_dL.diminfo[0].shape = __pyx_pybuffernd_dL.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd_dL.diminfo[1].strides = __pyx_pybuffernd_dL.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd_dL.diminfo[1].shape = __pyx_pybuffernd_dL.rcbuffer->pybuffer.shape[1]; { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_L.rcbuffer->pybuffer, (PyObject*)__pyx_v_L, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 82; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_L.rcbuffer->pybuffer, (PyObject*)__pyx_v_L, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_pybuffernd_L.diminfo[0].strides = __pyx_pybuffernd_L.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_L.diminfo[0].shape = __pyx_pybuffernd_L.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd_L.diminfo[1].strides = __pyx_pybuffernd_L.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd_L.diminfo[1].shape = __pyx_pybuffernd_L.rcbuffer->pybuffer.shape[1]; - /* "GPy/util/choleskies_cython.pyx":83 + /* "GPy/util/choleskies_cython.pyx":84 * * def backprop_gradient_par_c(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] L): * cdef np.ndarray[double, ndim=2] dL_dK = np.tril(dL) # makes a copy, c-contig # <<<<<<<<<<<<<< * cdef int N = L.shape[0] - * chol_backprop(N, dL_dK.data, L.data) + * with nogil: */ - __pyx_t_2 = __Pyx_GetModuleGlobalName(__pyx_n_s_np); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = __Pyx_GetModuleGlobalName(__pyx_n_s_np); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 84; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); - __pyx_t_3 = __Pyx_PyObject_GetAttrStr(__pyx_t_2, __pyx_n_s_tril); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyObject_GetAttrStr(__pyx_t_2, __pyx_n_s_tril); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 84; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __pyx_t_2 = NULL; @@ -3419,27 +3432,27 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_8backprop_gradient_par_ } } if (!__pyx_t_2) { - __pyx_t_1 = __Pyx_PyObject_CallOneArg(__pyx_t_3, ((PyObject *)__pyx_v_dL)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_CallOneArg(__pyx_t_3, ((PyObject *)__pyx_v_dL)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; 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goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; } __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 84; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_5 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_dL_dK.rcbuffer->pybuffer, (PyObject*)__pyx_t_5, &__Pyx_TypeInfo_double, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) { __pyx_v_dL_dK = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_dL_dK.rcbuffer->pybuffer.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 84; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_pybuffernd_dL_dK.diminfo[0].strides = __pyx_pybuffernd_dL_dK.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_dL_dK.diminfo[0].shape = __pyx_pybuffernd_dL_dK.rcbuffer->pybuffer.shape[0]; __pyx_pybuffernd_dL_dK.diminfo[1].strides = __pyx_pybuffernd_dL_dK.rcbuffer->pybuffer.strides[1]; __pyx_pybuffernd_dL_dK.diminfo[1].shape = __pyx_pybuffernd_dL_dK.rcbuffer->pybuffer.shape[1]; } } @@ -3447,36 +3460,70 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_8backprop_gradient_par_ __pyx_v_dL_dK = ((PyArrayObject *)__pyx_t_1); __pyx_t_1 = 0; - /* "GPy/util/choleskies_cython.pyx":84 + /* "GPy/util/choleskies_cython.pyx":85 * def backprop_gradient_par_c(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] L): * cdef np.ndarray[double, ndim=2] dL_dK = np.tril(dL) # makes a copy, c-contig * cdef int N = L.shape[0] # <<<<<<<<<<<<<< - * chol_backprop(N, dL_dK.data, L.data) - * return dL_dK + * with nogil: + * chol_backprop(N, dL_dK.data, L.data) */ __pyx_v_N = (__pyx_v_L->dimensions[0]); 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if (unlikely(!__pyx_tuple__26)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 82; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_tuple__26 = PyTuple_Pack(4, __pyx_n_s_dL, __pyx_n_s_L, __pyx_n_s_dL_dK, __pyx_n_s_N); if (unlikely(!__pyx_tuple__26)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_tuple__26); __Pyx_GIVEREF(__pyx_tuple__26); - __pyx_codeobj__27 = (PyObject*)__Pyx_PyCode_New(2, 0, 4, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__26, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_home_james_work_GPy_GPy_util_ch, __pyx_n_s_backprop_gradient_par_c, 82, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__27)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 82; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_codeobj__27 = (PyObject*)__Pyx_PyCode_New(2, 0, 4, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__26, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_Users_james_work_GPy_GPy_util_c, __pyx_n_s_backprop_gradient_par_c, 83, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__27)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + + /* "GPy/util/choleskies_cython.pyx":92 + * + * # TODO: with the next release of cython, cimport scipy.linalg.cython_blas as blas, then blas the hell out of this. + * def backprop_gradient_par2(double[:,:] dL, double[:,:] L): # <<<<<<<<<<<<<< + * """ + * a very slow implementation, but the clearest I hope + */ + __pyx_tuple__28 = PyTuple_Pack(9, __pyx_n_s_dL, __pyx_n_s_L, __pyx_n_s_dL_dK, __pyx_n_s_N, __pyx_n_s_k, __pyx_n_s_j, __pyx_n_s_i, __pyx_n_s_iN, __pyx_n_s_kN); if (unlikely(!__pyx_tuple__28)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 92; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__28); + __Pyx_GIVEREF(__pyx_tuple__28); + __pyx_codeobj__29 = (PyObject*)__Pyx_PyCode_New(2, 0, 9, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__28, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_Users_james_work_GPy_GPy_util_c, __pyx_n_s_backprop_gradient_par2, 92, __pyx_empty_bytes); 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__pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__32); + __Pyx_GIVEREF(__pyx_tuple__32); /* "View.MemoryView":281 * @@ -17269,9 +17933,9 @@ static int __Pyx_InitCachedConstants(void) { * cdef indirect_contiguous = Enum("") * */ - __pyx_tuple__31 = PyTuple_Pack(1, __pyx_kp_s_contiguous_and_direct); if (unlikely(!__pyx_tuple__31)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 281; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __Pyx_GOTREF(__pyx_tuple__31); - __Pyx_GIVEREF(__pyx_tuple__31); + __pyx_tuple__33 = PyTuple_Pack(1, __pyx_kp_s_contiguous_and_direct); if (unlikely(!__pyx_tuple__33)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 281; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__33); + __Pyx_GIVEREF(__pyx_tuple__33); /* "View.MemoryView":282 * @@ -17280,9 +17944,9 @@ static int __Pyx_InitCachedConstants(void) { * * */ - __pyx_tuple__32 = PyTuple_Pack(1, __pyx_kp_s_contiguous_and_indirect); if (unlikely(!__pyx_tuple__32)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __Pyx_GOTREF(__pyx_tuple__32); - __Pyx_GIVEREF(__pyx_tuple__32); + __pyx_tuple__34 = PyTuple_Pack(1, __pyx_kp_s_contiguous_and_indirect); if (unlikely(!__pyx_tuple__34)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_tuple__34); + __Pyx_GIVEREF(__pyx_tuple__34); __Pyx_RefNannyFinishContext(); return 0; __pyx_L1_error:; @@ -17496,16 +18160,28 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void) if (PyDict_SetItem(__pyx_d, __pyx_n_s_backprop_gradient_par, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 62; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "GPy/util/choleskies_cython.pyx":82 + /* "GPy/util/choleskies_cython.pyx":83 * void chol_backprop(int N, double* dL, double* L) * * def backprop_gradient_par_c(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] L): # <<<<<<<<<<<<<< * cdef np.ndarray[double, ndim=2] dL_dK = np.tril(dL) # makes a copy, c-contig * cdef int N = L.shape[0] */ - __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_17choleskies_cython_9backprop_gradient_par_c, NULL, __pyx_n_s_GPy_util_choleskies_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 82; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_17choleskies_cython_9backprop_gradient_par_c, NULL, __pyx_n_s_GPy_util_choleskies_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_d, __pyx_n_s_backprop_gradient_par_c, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 82; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_d, __pyx_n_s_backprop_gradient_par_c, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; + + /* "GPy/util/choleskies_cython.pyx":92 + * + * # TODO: with the next release of cython, cimport scipy.linalg.cython_blas as blas, then blas the hell out of this. + * def backprop_gradient_par2(double[:,:] dL, double[:,:] L): # <<<<<<<<<<<<<< + * """ + * a very slow implementation, but the clearest I hope + */ + __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_17choleskies_cython_11backprop_gradient_par2, NULL, __pyx_n_s_GPy_util_choleskies_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 92; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __Pyx_GOTREF(__pyx_t_1); + if (PyDict_SetItem(__pyx_d, __pyx_n_s_backprop_gradient_par2, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 92; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "GPy/util/choleskies_cython.pyx":1 @@ -17538,7 +18214,7 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void) * cdef strided = Enum("") # default * cdef indirect = Enum("") */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__28, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__30, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_XGOTREF(generic); __Pyx_DECREF_SET(generic, __pyx_t_1); @@ -17552,7 +18228,7 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void) * cdef indirect = Enum("") * */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__29, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 277; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__31, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 277; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_XGOTREF(strided); __Pyx_DECREF_SET(strided, __pyx_t_1); @@ -17566,7 +18242,7 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void) * * */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__30, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__32, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 278; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_XGOTREF(indirect); __Pyx_DECREF_SET(indirect, __pyx_t_1); @@ -17580,7 +18256,7 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void) * cdef indirect_contiguous = Enum("") * */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__31, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 281; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__33, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 281; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_XGOTREF(contiguous); __Pyx_DECREF_SET(contiguous, __pyx_t_1); @@ -17594,7 +18270,7 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void) * * */ - __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__32, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)((PyObject *)__pyx_MemviewEnum_type)), __pyx_tuple__34, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_XGOTREF(indirect_contiguous); __Pyx_DECREF_SET(indirect_contiguous, __pyx_t_1); diff --git a/GPy/util/choleskies_cython.pyx b/GPy/util/choleskies_cython.pyx index 50fa6709..bd6069b9 100644 --- a/GPy/util/choleskies_cython.pyx +++ b/GPy/util/choleskies_cython.pyx @@ -76,12 +76,36 @@ def backprop_gradient_par(double[:,:] dL, double[:,:] L): dL_dK[k, k] /= (2. * L[k, k]) return dL_dK -cdef extern from "cholesky_backprop.h": +#here's a pure C version... +cdef extern from "cholesky_backprop.h" nogil: void chol_backprop(int N, double* dL, double* L) def backprop_gradient_par_c(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] L): cdef np.ndarray[double, ndim=2] dL_dK = np.tril(dL) # makes a copy, c-contig cdef int N = L.shape[0] - chol_backprop(N, dL_dK.data, L.data) + with nogil: + chol_backprop(N, dL_dK.data, L.data) return dL_dK + +# TODO: with the next release of cython, cimport scipy.linalg.cython_blas as blas, then blas the hell out of this. +def backprop_gradient_par2(double[:,:] dL, double[:,:] L): + """ + a very slow implementation, but the clearest I hope + """ + cdef double[:,:] dL_dK = np.tril(dL).copy() + cdef int N = L.shape[0] + cdef int k, j, i, iN, kN + for k in range(N - 1, -1, -1): + #pragma this loop: + for i in range(k+1, N): + dL_dK[i,+k] -= np.dot(dL_dK[i,k+1:], L[k+1:,k]) + dL_dK[i,+k] -= np.dot(dL_dK[i:,i], L[i:,k]) + + for i in range(k+1, N): + dL_dK[i, k] /= L[k, k]; + dL_dK[k, k] -= L[i, k] * dL_dK[i, k]; + + dL_dK[k, k] /= (2. * L[k, k]); + return np.asarray(dL_dK) + diff --git a/GPy/util/cholesky_backprop.c b/GPy/util/cholesky_backprop.c index e3919abb..975e63cc 100644 --- a/GPy/util/cholesky_backprop.c +++ b/GPy/util/cholesky_backprop.c @@ -1,22 +1,32 @@ +#include +double mydot(int n, double* a, int stride_a, double* b, int stride_b){ + double ret = 0; + for(int i=0; i(-1);k--){ - #pragma omp parallel for private(i,j) - for(i=k+1;i(-1);k--){ + kN = k*N; + #pragma omp parallel for private(iN) + for(int i=k+1; i Date: Thu, 11 Jun 2015 18:00:47 +0100 Subject: [PATCH 35/41] lots of work on cython choleskies --- GPy/util/choleskies_cython.c | 739 +++++++++------------------------ GPy/util/choleskies_cython.pyx | 30 +- GPy/util/cholesky_backprop.c | 39 +- GPy/util/cholesky_backprop.h | 3 + setup.py | 2 +- 5 files changed, 243 insertions(+), 570 deletions(-) diff --git a/GPy/util/choleskies_cython.c b/GPy/util/choleskies_cython.c index db7d1aed..21492a88 100644 --- a/GPy/util/choleskies_cython.c +++ b/GPy/util/choleskies_cython.c @@ -1470,7 +1470,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_2triang_to_flat(CYTHON_ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_4backprop_gradient(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_dL, PyArrayObject *__pyx_v_L); /* proto */ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_dL, __Pyx_memviewslice __pyx_v_L); /* proto */ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_8backprop_gradient_par_c(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_dL, PyArrayObject *__pyx_v_L); /* proto */ -static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_10backprop_gradient_par2(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_dL, __Pyx_memviewslice __pyx_v_L); /* proto */ +static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_10backprop_gradient_par_c_old(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_dL, PyArrayObject *__pyx_v_L); /* proto */ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */ static int __pyx_array_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ @@ -1534,12 +1534,9 @@ static char __pyx_k_Zd[] = "Zd"; static char __pyx_k_Zf[] = "Zf"; static char __pyx_k_Zg[] = "Zg"; static char __pyx_k_dL[] = "dL"; -static char __pyx_k_iN[] = "iN"; static char __pyx_k_id[] = "id"; -static char __pyx_k_kN[] = "kN"; static char __pyx_k_mm[] = "mm"; static char __pyx_k_np[] = "np"; -static char __pyx_k_dot[] = "dot"; static char __pyx_k_obj[] = "obj"; static char __pyx_k_ret[] = "ret"; static char __pyx_k_base[] = "base"; @@ -1572,7 +1569,6 @@ static char __pyx_k_name_2[] = "__name__"; static char __pyx_k_struct[] = "struct"; static char __pyx_k_unpack[] = "unpack"; static char __pyx_k_xrange[] = "xrange"; -static char __pyx_k_asarray[] = "asarray"; static char __pyx_k_fortran[] = "fortran"; static char __pyx_k_memview[] = "memview"; static char __pyx_k_Ellipsis[] = "Ellipsis"; @@ -1595,7 +1591,6 @@ static char __pyx_k_strided_and_indirect[] = ""; static char __pyx_k_backprop_gradient_par[] = "backprop_gradient_par"; static char __pyx_k_contiguous_and_direct[] = ""; static char __pyx_k_MemoryView_of_r_object[] = ""; -static char __pyx_k_backprop_gradient_par2[] = "backprop_gradient_par2"; static char __pyx_k_MemoryView_of_r_at_0x_x[] = ""; static char __pyx_k_backprop_gradient_par_c[] = "backprop_gradient_par_c"; static char __pyx_k_contiguous_and_indirect[] = ""; @@ -1606,11 +1601,12 @@ static char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d. static char __pyx_k_GPy_util_choleskies_cython[] = "GPy.util.choleskies_cython"; static char __pyx_k_Index_out_of_bounds_axis_d[] = "Index out of bounds (axis %d)"; static char __pyx_k_Step_may_not_be_zero_axis_d[] = "Step may not be zero (axis %d)"; +static char __pyx_k_backprop_gradient_par_c_old[] = "backprop_gradient_par_c_old"; static char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array"; static char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous"; static char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; static char __pyx_k_strided_and_direct_or_indirect[] = ""; -static char __pyx_k_Users_james_work_GPy_GPy_util_c[] = "/Users/james/work/GPy/GPy/util/choleskies_cython.pyx"; +static char __pyx_k_home_james_work_GPy_GPy_util_ch[] = "/home/james/work/GPy/GPy/util/choleskies_cython.pyx"; static char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)"; static char __pyx_k_All_dimensions_preceding_dimensi[] = "All dimensions preceding dimension %d must be indexed and not sliced"; static char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; @@ -1652,14 +1648,12 @@ static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a; static PyObject *__pyx_n_s_RuntimeError; static PyObject *__pyx_n_s_TypeError; static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object; -static PyObject *__pyx_kp_s_Users_james_work_GPy_GPy_util_c; static PyObject *__pyx_n_s_ValueError; static PyObject *__pyx_n_s_allocate_buffer; -static PyObject *__pyx_n_s_asarray; static PyObject *__pyx_n_s_backprop_gradient; static PyObject *__pyx_n_s_backprop_gradient_par; -static PyObject *__pyx_n_s_backprop_gradient_par2; static PyObject *__pyx_n_s_backprop_gradient_par_c; +static PyObject *__pyx_n_s_backprop_gradient_par_c_old; static PyObject *__pyx_n_s_base; static PyObject *__pyx_n_s_c; static PyObject *__pyx_n_u_c; @@ -1671,7 +1665,6 @@ static PyObject *__pyx_n_s_count; static PyObject *__pyx_n_s_d; static PyObject *__pyx_n_s_dL; static PyObject *__pyx_n_s_dL_dK; -static PyObject *__pyx_n_s_dot; static PyObject *__pyx_n_s_dtype_is_object; static PyObject *__pyx_n_s_empty; static PyObject *__pyx_n_s_enumerate; @@ -1683,15 +1676,14 @@ static PyObject *__pyx_n_s_format; static PyObject *__pyx_n_s_fortran; static PyObject *__pyx_n_u_fortran; static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi; +static PyObject *__pyx_kp_s_home_james_work_GPy_GPy_util_ch; static PyObject *__pyx_n_s_i; -static PyObject *__pyx_n_s_iN; static PyObject *__pyx_n_s_id; static PyObject *__pyx_n_s_import; static PyObject *__pyx_n_s_itemsize; static PyObject *__pyx_kp_s_itemsize_0_for_cython_array; static PyObject *__pyx_n_s_j; static PyObject *__pyx_n_s_k; -static PyObject *__pyx_n_s_kN; static PyObject *__pyx_n_s_m; static PyObject *__pyx_n_s_main; static PyObject *__pyx_n_s_memview; @@ -3056,7 +3048,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_6backprop_gradient_par( #define unlikely(x) (x) #endif #ifdef _OPENMP - #pragma omp parallel private(__pyx_t_9, __pyx_t_25, __pyx_t_20, __pyx_t_16, __pyx_t_21, __pyx_t_17, __pyx_t_14, __pyx_t_19, __pyx_t_22, __pyx_t_10, __pyx_t_11, __pyx_t_23, __pyx_t_13, __pyx_t_12, __pyx_t_18, __pyx_t_24, __pyx_t_26, __pyx_t_15, __pyx_t_27) + #pragma omp parallel private(__pyx_t_17, __pyx_t_14, __pyx_t_20, __pyx_t_26, __pyx_t_22, __pyx_t_10, __pyx_t_11, __pyx_t_23, __pyx_t_9, __pyx_t_25, __pyx_t_16, __pyx_t_21, __pyx_t_19, __pyx_t_27, __pyx_t_15, __pyx_t_13, __pyx_t_12, __pyx_t_18, __pyx_t_24) #endif /* _OPENMP */ { @@ -3516,7 +3508,7 @@ static PyObject *__pyx_pf_3GPy_4util_17choleskies_cython_8backprop_gradient_par_ * chol_backprop(N, dL_dK.data, L.data) * return dL_dK # <<<<<<<<<<<<<< * - * + * cdef extern from "cholesky_backprop.h" nogil: */ __Pyx_XDECREF(__pyx_r); 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if (unlikely(!__pyx_codeobj__29)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 93; __pyx_clineno = __LINE__; goto __pyx_L1_error;} /* "View.MemoryView":276 * return self.name @@ -18172,16 +17827,16 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void) if (PyDict_SetItem(__pyx_d, __pyx_n_s_backprop_gradient_par_c, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "GPy/util/choleskies_cython.pyx":92 + /* "GPy/util/choleskies_cython.pyx":93 + * void old_chol_backprop(int N, double* dL, double* L) * - * # TODO: with the next release of cython, cimport scipy.linalg.cython_blas as blas, then blas the hell out of this. - * def backprop_gradient_par2(double[:,:] dL, double[:,:] L): # <<<<<<<<<<<<<< - * """ - * a very slow implementation, but the clearest I hope + * def backprop_gradient_par_c_old(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] L): # <<<<<<<<<<<<<< + * cdef np.ndarray[double, ndim=2] dL_dK = np.tril(dL) # makes a copy, c-contig + * cdef int N = L.shape[0] */ - __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_17choleskies_cython_11backprop_gradient_par2, NULL, __pyx_n_s_GPy_util_choleskies_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 92; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_3GPy_4util_17choleskies_cython_11backprop_gradient_par_c_old, NULL, __pyx_n_s_GPy_util_choleskies_cython); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 93; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (PyDict_SetItem(__pyx_d, __pyx_n_s_backprop_gradient_par2, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 92; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_d, __pyx_n_s_backprop_gradient_par_c_old, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 93; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "GPy/util/choleskies_cython.pyx":1 diff --git a/GPy/util/choleskies_cython.pyx b/GPy/util/choleskies_cython.pyx index bd6069b9..d85b19cf 100644 --- a/GPy/util/choleskies_cython.pyx +++ b/GPy/util/choleskies_cython.pyx @@ -87,25 +87,21 @@ def backprop_gradient_par_c(np.ndarray[double, ndim=2] dL, np.ndarray[double, nd chol_backprop(N, dL_dK.data, L.data) return dL_dK +cdef extern from "cholesky_backprop.h" nogil: + void old_chol_backprop(int N, double* dL, double* L) -# TODO: with the next release of cython, cimport scipy.linalg.cython_blas as blas, then blas the hell out of this. -def backprop_gradient_par2(double[:,:] dL, double[:,:] L): - """ - a very slow implementation, but the clearest I hope - """ - cdef double[:,:] dL_dK = np.tril(dL).copy() +def backprop_gradient_par_c_old(np.ndarray[double, ndim=2] dL, np.ndarray[double, ndim=2] L): + cdef np.ndarray[double, ndim=2] dL_dK = np.tril(dL) # makes a copy, c-contig cdef int N = L.shape[0] - cdef int k, j, i, iN, kN - for k in range(N - 1, -1, -1): - #pragma this loop: - for i in range(k+1, N): - dL_dK[i,+k] -= np.dot(dL_dK[i,k+1:], L[k+1:,k]) - dL_dK[i,+k] -= np.dot(dL_dK[i:,i], L[i:,k]) + with nogil: + old_chol_backprop(N, dL_dK.data, L.data) + return dL_dK + + + + + + - for i in range(k+1, N): - dL_dK[i, k] /= L[k, k]; - dL_dK[k, k] -= L[i, k] * dL_dK[i, k]; - dL_dK[k, k] /= (2. * L[k, k]); - return np.asarray(dL_dK) diff --git a/GPy/util/cholesky_backprop.c b/GPy/util/cholesky_backprop.c index 975e63cc..0a4a2f03 100644 --- a/GPy/util/cholesky_backprop.c +++ b/GPy/util/cholesky_backprop.c @@ -1,4 +1,25 @@ -#include +#include +void chol_backprop(int N, double* dL, double* L){ + //at the input to this fn, dL is df_dL. after this fn is complet, dL is df_dK + int i,k; + + dL[N*N - 1] /= (2. * L[N*N - 1]); + for(k=N-2;k>(-1);k--){ + cblas_dsymv(CblasRowMajor, CblasLower, + N-k-1, -1, + &dL[(N*(k+1) + k+1)],N, + &L[k*N+k+1],1, + 1, &dL[N*(k+1)+k], N); + for(i=0;i<(N-k-1); i++){ + dL[N*(k+1+i)+k] -= dL[N*(k+1)+k+i*(N+1)+1] * L[k*N+k+1+i]; + } + + cblas_dscal(N-k-1, 1.0/L[k*N+k], &dL[(k+1)*N+k], N); + dL[k*N + k] -= cblas_ddot(N-k-1, &dL[(k+1)*N+k], N, &L[k*N+k+1], 1); + dL[k*N + k] /= (2.0 * L[k*N + k]); + } +} + double mydot(int n, double* a, int stride_a, double* b, int stride_b){ double ret = 0; for(int i=0; i(-1);k--){ + int iN, kN,i,j,k; + dL[N*N-1] /= (2. * U[N*N-1]); + for(k=N-2;k>(-1);k--){ kN = k*N; - #pragma omp parallel for private(iN) - for(int i=k+1; i + +void dsymv(int N, double*A, double*b, double*y); double mydot(int n, double* a, int stride_a, double* b, int stride_b); void chol_backprop(int N, double* dL, double* L); diff --git a/setup.py b/setup.py index e12cbaa4..8025cd5d 100644 --- a/setup.py +++ b/setup.py @@ -22,7 +22,7 @@ ext_mods = [Extension(name='GPy.kern._src.stationary_cython', Extension(name='GPy.util.choleskies_cython', sources=['GPy/util/choleskies_cython.c', 'GPy/util/cholesky_backprop.c'], include_dirs=[np.get_include()], - extra_link_args = ['-lgomp'], + extra_link_args = ['-lgomp', '-lblas'], extra_compile_args=compile_flags+['-std=c99']), Extension(name='GPy.util.linalg_cython', sources=['GPy/util/linalg_cython.c'], From 24e759199e5d51143af91f56b2aa8a046895ef9e Mon Sep 17 00:00:00 2001 From: James Hensman Date: Fri, 12 Jun 2015 16:58:29 +0100 Subject: [PATCH 36/41] sqrt pi term was missing in variational expectations --- GPy/likelihoods/likelihood.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/likelihoods/likelihood.py b/GPy/likelihoods/likelihood.py index 31f5dffd..73118569 100644 --- a/GPy/likelihoods/likelihood.py +++ b/GPy/likelihoods/likelihood.py @@ -267,7 +267,7 @@ class Likelihood(Parameterized): if self.size: dF_dtheta = self.dlogpdf_dtheta(X, Y[:,None]) # Ntheta x (orig size) x N_{quad_points} - dF_dtheta = np.dot(dF_dtheta, gh_w) + dF_dtheta = np.dot(dF_dtheta, gh_w)/np.sqrt(np.pi) dF_dtheta = dF_dtheta.reshape(self.size, shape[0], shape[1]) else: dF_dtheta = None # Not yet implemented From e58cc51c4704438b096a0cf519e67e0bde10b4d6 Mon Sep 17 00:00:00 2001 From: javiergonzalezh Date: Mon, 15 Jun 2015 18:42:29 +0100 Subject: [PATCH 37/41] allowing set initial noise variance for GPRegression --- GPy/models/gp_regression.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/GPy/models/gp_regression.py b/GPy/models/gp_regression.py index 7b8fb63f..105a63e7 100644 --- a/GPy/models/gp_regression.py +++ b/GPy/models/gp_regression.py @@ -16,6 +16,7 @@ class GPRegression(GP): :param Y: observed values :param kernel: a GPy kernel, defaults to rbf :param Norm normalizer: [False] + :param noise_var: the noise variance for Gaussian likelhood, defaults to 1. Normalize Y with the norm given. If normalizer is False, no normalization will be done @@ -25,12 +26,12 @@ class GPRegression(GP): """ - def __init__(self, X, Y, kernel=None, Y_metadata=None, normalizer=None): + def __init__(self, X, Y, kernel=None, Y_metadata=None, normalizer=None, noise_var=1.): if kernel is None: kernel = kern.RBF(X.shape[1]) - - likelihood = likelihoods.Gaussian() + + likelihood = likelihoods.Gaussian(variance=noise_var) super(GPRegression, self).__init__(X, Y, kernel, likelihood, name='GP regression', Y_metadata=Y_metadata, normalizer=normalizer) From e7d1277e625f3df1c9a2b492bf0ab6c6f490235c Mon Sep 17 00:00:00 2001 From: Mike Croucher Date: Tue, 23 Jun 2015 01:26:52 -0700 Subject: [PATCH 38/41] Python 3 fixes --- GPy/core/parameterization/index_operations.py | 2 +- GPy/core/parameterization/parameterized.py | 4 +- GPy/core/parameterization/priors.py | 38 +++++++++---------- GPy/core/parameterization/transformations.py | 4 +- GPy/inference/optimization/optimization.py | 2 +- GPy/kern/__init__.py | 2 +- GPy/kern/_src/coregionalize.py | 2 +- GPy/kern/_src/independent_outputs.py | 2 +- GPy/kern/_src/stationary.py | 2 +- GPy/models/dpgplvm.py | 4 +- GPy/models/gp_regression.py | 2 +- GPy/models/gradient_checker.py | 12 +++--- GPy/testing/link_function_tests.py | 2 +- GPy/util/block_matrices.py | 4 +- GPy/util/choleskies.py | 10 ++--- GPy/util/linalg.py | 2 +- README.md | 6 ++- 17 files changed, 52 insertions(+), 48 deletions(-) diff --git a/GPy/core/parameterization/index_operations.py b/GPy/core/parameterization/index_operations.py index 5c3e350f..ae04b2ee 100644 --- a/GPy/core/parameterization/index_operations.py +++ b/GPy/core/parameterization/index_operations.py @@ -5,7 +5,7 @@ import numpy from numpy.lib.function_base import vectorize from .lists_and_dicts import IntArrayDict from functools import reduce -from transformations import Transformation +from .transformations import Transformation def extract_properties_to_index(index, props): prop_index = dict() diff --git a/GPy/core/parameterization/parameterized.py b/GPy/core/parameterization/parameterized.py index d2d06fe3..96810927 100644 --- a/GPy/core/parameterization/parameterized.py +++ b/GPy/core/parameterization/parameterized.py @@ -6,10 +6,10 @@ import numpy; np = numpy import itertools from re import compile, _pattern_type from .param import ParamConcatenation -from parameter_core import HierarchyError, Parameterizable, adjust_name_for_printing +from .parameter_core import HierarchyError, Parameterizable, adjust_name_for_printing import logging -from index_operations import ParameterIndexOperationsView +from .index_operations import ParameterIndexOperationsView logger = logging.getLogger("parameters changed meta") class ParametersChangedMeta(type): diff --git a/GPy/core/parameterization/priors.py b/GPy/core/parameterization/priors.py index 3a213fcd..c748f0df 100644 --- a/GPy/core/parameterization/priors.py +++ b/GPy/core/parameterization/priors.py @@ -758,12 +758,12 @@ class DGPLVM_Lamda(Prior, Parameterized): self.sigma2 = sigma2 # self.x = x self.lbl = lbl - self.lamda = lamda + self.lamda = lamda self.classnum = lbl.shape[1] self.datanum = lbl.shape[0] self.x_shape = x_shape self.dim = x_shape[1] - self.lamda = Param('lamda', np.diag(lamda)) + self.lamda = Param('lamda', np.diag(lamda)) self.link_parameter(self.lamda) def get_class_label(self, y): @@ -789,7 +789,7 @@ class DGPLVM_Lamda(Prior, Parameterized): M_i = np.zeros((self.classnum, self.dim)) for i in cls: # Mean of each class - class_i = cls[i] + class_i = cls[i] M_i[i] = np.mean(class_i, axis=0) return M_i @@ -899,8 +899,8 @@ class DGPLVM_Lamda(Prior, Parameterized): #!!!!!!!!!!!!!!!!!!!!!!!!!!! #self.lamda.values[:] = self.lamda.values/self.lamda.values.sum() - xprime = x.dot(np.diagflat(self.lamda)) - x = xprime + xprime = x.dot(np.diagflat(self.lamda)) + x = xprime # print x cls = self.compute_cls(x) M_0 = np.mean(x, axis=0) @@ -910,14 +910,14 @@ class DGPLVM_Lamda(Prior, Parameterized): # Sb_inv_N = np.linalg.inv(Sb + np.eye(Sb.shape[0]) * (np.diag(Sb).min() * 0.1)) #Sb_inv_N = np.linalg.inv(Sb+np.eye(Sb.shape[0])*0.1) #Sb_inv_N = pdinv(Sb+ np.eye(Sb.shape[0]) * (np.diag(Sb).min() * 0.1))[0] - Sb_inv_N = pdinv(Sb + np.eye(Sb.shape[0])*0.1)[0] + Sb_inv_N = pdinv(Sb + np.eye(Sb.shape[0])*0.1)[0] return (-1 / self.sigma2) * np.trace(Sb_inv_N.dot(Sw)) # This function calculates derivative of the log of prior function def lnpdf_grad(self, x): x = x.reshape(self.x_shape) - xprime = x.dot(np.diagflat(self.lamda)) - x = xprime + xprime = x.dot(np.diagflat(self.lamda)) + x = xprime # print x cls = self.compute_cls(x) M_0 = np.mean(x, axis=0) @@ -934,7 +934,7 @@ class DGPLVM_Lamda(Prior, Parameterized): # Sb_inv_N = np.linalg.inv(Sb + np.eye(Sb.shape[0]) * (np.diag(Sb).min() * 0.1)) #Sb_inv_N = np.linalg.inv(Sb+np.eye(Sb.shape[0])*0.1) #Sb_inv_N = pdinv(Sb+ np.eye(Sb.shape[0]) * (np.diag(Sb).min() * 0.1))[0] - Sb_inv_N = pdinv(Sb + np.eye(Sb.shape[0])*0.1)[0] + Sb_inv_N = pdinv(Sb + np.eye(Sb.shape[0])*0.1)[0] Sb_inv_N_trans = np.transpose(Sb_inv_N) Sb_inv_N_trans_minus = -1 * Sb_inv_N_trans Sw_trans = np.transpose(Sw) @@ -951,14 +951,14 @@ class DGPLVM_Lamda(Prior, Parameterized): # Because of the GPy we need to transpose our matrix so that it gets the same shape as out matrix (denominator layout!!!) DPxprim_Dx = DPxprim_Dx.T - DPxprim_Dlamda = DPx_Dx.dot(x) + DPxprim_Dlamda = DPx_Dx.dot(x) # Because of the GPy we need to transpose our matrix so that it gets the same shape as out matrix (denominator layout!!!) - DPxprim_Dlamda = DPxprim_Dlamda.T + DPxprim_Dlamda = DPxprim_Dlamda.T - self.lamda.gradient = np.diag(DPxprim_Dlamda) + self.lamda.gradient = np.diag(DPxprim_Dlamda) # print DPxprim_Dx - return DPxprim_Dx + return DPxprim_Dx # def frb(self, x): @@ -1139,8 +1139,8 @@ class DGPLVM_T(Prior): # This function calculates log of our prior def lnpdf(self, x): x = x.reshape(self.x_shape) - xprim = x.dot(self.vec) - x = xprim + xprim = x.dot(self.vec) + x = xprim # print x cls = self.compute_cls(x) M_0 = np.mean(x, axis=0) @@ -1156,11 +1156,11 @@ class DGPLVM_T(Prior): # This function calculates derivative of the log of prior function def lnpdf_grad(self, x): - x = x.reshape(self.x_shape) - xprim = x.dot(self.vec) - x = xprim + x = x.reshape(self.x_shape) + xprim = x.dot(self.vec) + x = xprim # print x - cls = self.compute_cls(x) + cls = self.compute_cls(x) M_0 = np.mean(x, axis=0) M_i = self.compute_Mi(cls) Sb = self.compute_Sb(cls, M_i, M_0) diff --git a/GPy/core/parameterization/transformations.py b/GPy/core/parameterization/transformations.py index d53cb6c8..01a1f44b 100644 --- a/GPy/core/parameterization/transformations.py +++ b/GPy/core/parameterization/transformations.py @@ -35,12 +35,12 @@ class Transformation(object): """ compute the log of the jacobian of f, evaluated at f(x)= model_param """ - raise NotImplementedError + raise NotImplementedError def log_jacobian_grad(self, model_param): """ compute the drivative of the log of the jacobian of f, evaluated at f(x)= model_param """ - raise NotImplementedError + raise NotImplementedError def gradfactor(self, model_param, dL_dmodel_param): """ df(opt_param)_dopt_param evaluated at self.f(opt_param)=model_param, times the gradient dL_dmodel_param, diff --git a/GPy/inference/optimization/optimization.py b/GPy/inference/optimization/optimization.py index fd140688..48bdd809 100644 --- a/GPy/inference/optimization/optimization.py +++ b/GPy/inference/optimization/optimization.py @@ -142,7 +142,7 @@ class opt_lbfgsb(Optimizer): #a more helpful error message is available in opt_result in the Error case if opt_result[2]['warnflag']==2: - self.status = 'Error' + opt_result[2]['task'] + self.status = 'Error' + str(opt_result[2]['task']) class opt_simplex(Optimizer): def __init__(self, *args, **kwargs): diff --git a/GPy/kern/__init__.py b/GPy/kern/__init__.py index 2bd55617..f479c387 100644 --- a/GPy/kern/__init__.py +++ b/GPy/kern/__init__.py @@ -19,5 +19,5 @@ from ._src.splitKern import SplitKern,DEtime from ._src.splitKern import DEtime as DiffGenomeKern -from _src.basis_funcs import LinearSlopeBasisFuncKernel, BasisFuncKernel, ChangePointBasisFuncKernel, DomainKernel +from ._src.basis_funcs import LinearSlopeBasisFuncKernel, BasisFuncKernel, ChangePointBasisFuncKernel, DomainKernel diff --git a/GPy/kern/_src/coregionalize.py b/GPy/kern/_src/coregionalize.py index 7d5f5a2b..3d71c99f 100644 --- a/GPy/kern/_src/coregionalize.py +++ b/GPy/kern/_src/coregionalize.py @@ -6,7 +6,7 @@ import numpy as np from ...core.parameterization import Param from ...core.parameterization.transformations import Logexp from ...util.config import config # for assesing whether to use cython -import coregionalize_cython +from . import coregionalize_cython class Coregionalize(Kern): """ diff --git a/GPy/kern/_src/independent_outputs.py b/GPy/kern/_src/independent_outputs.py index 6f8b7be1..9ebb5711 100644 --- a/GPy/kern/_src/independent_outputs.py +++ b/GPy/kern/_src/independent_outputs.py @@ -105,7 +105,7 @@ class IndependentOutputs(CombinationKernel): if X2 is None: # TODO: make use of index_to_slices # FIXME: Broken as X is already sliced out - print "Warning, gradients_X may not be working, I believe X has already been sliced out by the slicer!" + print("Warning, gradients_X may not be working, I believe X has already been sliced out by the slicer!") values = np.unique(X[:,self.index_dim]) slices = [X[:,self.index_dim]==i for i in values] [target.__setitem__(s, kern.gradients_X(dL_dK[s,s],X[s],None)) diff --git a/GPy/kern/_src/stationary.py b/GPy/kern/_src/stationary.py index df064de7..e69e316b 100644 --- a/GPy/kern/_src/stationary.py +++ b/GPy/kern/_src/stationary.py @@ -13,7 +13,7 @@ from ...util.config import config # for assesing whether to use cython from ...util.caching import Cache_this try: - import stationary_cython + from . import stationary_cython except ImportError: print('warning in sationary: failed to import cython module: falling back to numpy') config.set('cython', 'working', 'false') diff --git a/GPy/models/dpgplvm.py b/GPy/models/dpgplvm.py index 1c5dccd0..7f947c53 100644 --- a/GPy/models/dpgplvm.py +++ b/GPy/models/dpgplvm.py @@ -3,7 +3,7 @@ import numpy as np from .. import kern -from bayesian_gplvm import BayesianGPLVM +from .bayesian_gplvm import BayesianGPLVM from ..core.parameterization.variational import NormalPosterior, NormalPrior class DPBayesianGPLVM(BayesianGPLVM): @@ -15,5 +15,5 @@ class DPBayesianGPLVM(BayesianGPLVM): name='bayesian gplvm', mpi_comm=None, normalizer=None, missing_data=False, stochastic=False, batchsize=1): super(DPBayesianGPLVM,self).__init__(Y=Y, input_dim=input_dim, X=X, X_variance=X_variance, init=init, num_inducing=num_inducing, Z=Z, kernel=kernel, inference_method=inference_method, likelihood=likelihood, mpi_comm=mpi_comm, normalizer=normalizer, missing_data=missing_data, stochastic=stochastic, batchsize=batchsize, name='dp bayesian gplvm') - self.X.mean.set_prior(X_prior) + self.X.mean.set_prior(X_prior) self.link_parameter(X_prior) diff --git a/GPy/models/gp_regression.py b/GPy/models/gp_regression.py index 105a63e7..7266ae92 100644 --- a/GPy/models/gp_regression.py +++ b/GPy/models/gp_regression.py @@ -31,7 +31,7 @@ class GPRegression(GP): if kernel is None: kernel = kern.RBF(X.shape[1]) - likelihood = likelihoods.Gaussian(variance=noise_var) + likelihood = likelihoods.Gaussian(variance=noise_var) super(GPRegression, self).__init__(X, Y, kernel, likelihood, name='GP regression', Y_metadata=Y_metadata, normalizer=normalizer) diff --git a/GPy/models/gradient_checker.py b/GPy/models/gradient_checker.py index c2cde834..728f3e23 100644 --- a/GPy/models/gradient_checker.py +++ b/GPy/models/gradient_checker.py @@ -228,14 +228,14 @@ class HessianChecker(GradientChecker): if verbose: if block_indices: - print "\nBlock {}".format(block_indices) + print("\nBlock {}".format(block_indices)) else: - print "\nAll blocks" + print("\nAll blocks") header = ['Checked', 'Max-Ratio', 'Min-Ratio', 'Min-Difference', 'Max-Difference'] header_string = map(lambda x: ' | '.join(header), [header]) separator = '-' * len(header_string[0]) - print '\n'.join([header_string[0], separator]) + print('\n'.join([header_string[0], separator])) min_r = '%.6f' % float(numpy.min(ratio)) max_r = '%.6f' % float(numpy.max(ratio)) max_d = '%.6f' % float(numpy.max(difference)) @@ -248,7 +248,7 @@ class HessianChecker(GradientChecker): checked = "\033[91m False \033[0m" grad_string = "{} | {} | {} | {} | {} ".format(checked, cols[0], cols[1], cols[2], cols[3]) - print grad_string + print(grad_string) if plot: import pylab as pb @@ -348,7 +348,7 @@ class SkewChecker(HessianChecker): numeric_hess_partial = nd.Jacobian(self._df, vectorized=True) numeric_hess = numeric_hess_partial(x) - print "Done making numerical hessian" + print("Done making numerical hessian") if analytic_hess.dtype is np.dtype('object'): #Blockify numeric_hess aswell blocksizes, pagesizes = get_block_shapes_3d(analytic_hess) @@ -365,7 +365,7 @@ class SkewChecker(HessianChecker): #Unless super_plot is set, just plot the first one p = True if (plot and block_ind == numeric_hess.shape[2]-1) or super_plot else False if verbose: - print "Checking derivative of hessian wrt parameter number {}".format(block_ind) + print("Checking derivative of hessian wrt parameter number {}".format(block_ind)) check_passed[block_ind] = self.checkgrad_block(analytic_hess[:,:,block_ind], numeric_hess[:,:,block_ind], verbose=verbose, step=step, tolerance=tolerance, block_indices=block_indices, plot=p) current_index += current_size diff --git a/GPy/testing/link_function_tests.py b/GPy/testing/link_function_tests.py index fb8fba99..e8cbbf66 100644 --- a/GPy/testing/link_function_tests.py +++ b/GPy/testing/link_function_tests.py @@ -49,7 +49,7 @@ class LinkFunctionTests(np.testing.TestCase): self.assertTrue(grad3.checkgrad(verbose=True)) if test_lim: - print "Testing limits" + print("Testing limits") #Remove some otherwise we are too close to the limit for gradcheck to work effectively lim_of_inf = lim_of_inf - 1e-4 grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=lim_of_inf) diff --git a/GPy/util/block_matrices.py b/GPy/util/block_matrices.py index e1e04aaa..8c0de67d 100644 --- a/GPy/util/block_matrices.py +++ b/GPy/util/block_matrices.py @@ -100,10 +100,10 @@ def block_dot(A, B, diagonal=False): Dshape = D.shape if diagonal and (len(Cshape) == 1 or len(Dshape) == 1\ or C.shape[0] != C.shape[1] or D.shape[0] != D.shape[1]): - print "Broadcasting, C: {} D:{}".format(C.shape, D.shape) + print("Broadcasting, C: {} D:{}".format(C.shape, D.shape)) return C*D else: - print "Dotting, C: {} C:{}".format(C.shape, D.shape) + print("Dotting, C: {} C:{}".format(C.shape, D.shape)) return np.dot(C,D) dot = np.vectorize(f, otypes = [np.object]) return dot(A,B) diff --git a/GPy/util/choleskies.py b/GPy/util/choleskies.py index a12631aa..f079cabd 100644 --- a/GPy/util/choleskies.py +++ b/GPy/util/choleskies.py @@ -5,7 +5,7 @@ import numpy as np from . import linalg from .config import config -import choleskies_cython +from . import choleskies_cython def safe_root(N): i = np.sqrt(N) @@ -59,12 +59,12 @@ def _backprop_gradient_pure(dL, L): """ dL_dK = np.tril(dL).copy() N = L.shape[0] - for k in xrange(N - 1, -1, -1): - for j in xrange(k + 1, N): - for i in xrange(j, N): + for k in range(N - 1, -1, -1): + for j in range(k + 1, N): + for i in range(j, N): dL_dK[i, k] -= dL_dK[i, j] * L[j, k] dL_dK[j, k] -= dL_dK[i, j] * L[i, k] - for j in xrange(k + 1, N): + for j in range(k + 1, N): dL_dK[j, k] /= L[k, k] dL_dK[k, k] -= L[j, k] * dL_dK[j, k] dL_dK[k, k] /= (2 * L[k, k]) diff --git a/GPy/util/linalg.py b/GPy/util/linalg.py index 634a1e0d..ed73d133 100644 --- a/GPy/util/linalg.py +++ b/GPy/util/linalg.py @@ -15,7 +15,7 @@ import warnings import os from .config import config import logging -import linalg_cython +from . import linalg_cython _scipyversion = np.float64((scipy.__version__).split('.')[:2]) diff --git a/README.md b/README.md index 60dcbe24..07a65cc6 100644 --- a/README.md +++ b/README.md @@ -13,7 +13,6 @@ Continuous integration status: ![CI status](https://travis-ci.org/SheffieldML/GP ### Python 3 Compatibility Work is underway to make GPy run on Python 3. -* Python 2.x compatibility is currently broken in this fork * All tests in the testsuite now run on Python3. To see this for yourself, in Ubuntu 14.04, you can do @@ -21,12 +20,17 @@ To see this for yourself, in Ubuntu 14.04, you can do git clone https://github.com/mikecroucher/GPy.git cd GPy git checkout devel + python3 setup.py build_ext --inplace nosetests3 GPy/testing nosetests3 is Ubuntu's way of reffering to the Python 3 version of nosetests. You install it with sudo apt-get install python3-nose +The command `python3 setup.py build_ext --inplace` builds the Cython extensions. IF it doesn't work, you may need to install this: + + sudo apt-get install python3-dev + * Test coverage is less than 100% so it is expected that there is still more work to be done. We need more tests and examples to try out. * All weave functions not covered by the test suite are *simply commented out*. Can add equivalents later as test functions become available * A set of benchmarks would be useful! From a1c9168de48d5a2138c057c4beea80830928a815 Mon Sep 17 00:00:00 2001 From: Alan Saul Date: Thu, 25 Jun 2015 15:18:08 +0100 Subject: [PATCH 39/41] Passing on y_metadata --- GPy/likelihoods/likelihood.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/likelihoods/likelihood.py b/GPy/likelihoods/likelihood.py index 73118569..d41468ab 100644 --- a/GPy/likelihoods/likelihood.py +++ b/GPy/likelihoods/likelihood.py @@ -266,7 +266,7 @@ class Likelihood(Parameterized): stop if self.size: - dF_dtheta = self.dlogpdf_dtheta(X, Y[:,None]) # Ntheta x (orig size) x N_{quad_points} + dF_dtheta = self.dlogpdf_dtheta(X, Y[:,None], Y_metadata=Y_metadata) # Ntheta x (orig size) x N_{quad_points} dF_dtheta = np.dot(dF_dtheta, gh_w)/np.sqrt(np.pi) dF_dtheta = dF_dtheta.reshape(self.size, shape[0], shape[1]) else: From 5cc17e87542da0ec1b41d3c159caeb22ac493cd2 Mon Sep 17 00:00:00 2001 From: Zhenwen Dai Date: Sun, 28 Jun 2015 21:33:57 +0100 Subject: [PATCH 40/41] some correction for ibp ssgplvm --- .../latent_function_inference/inferenceX.py | 24 ++++++++++++------- GPy/kern/_src/rbf.py | 2 +- GPy/models/bayesian_gplvm_minibatch.py | 3 --- GPy/plotting/matplot_dep/visualize.py | 20 +++++++++++----- 4 files changed, 30 insertions(+), 19 deletions(-) diff --git a/GPy/inference/latent_function_inference/inferenceX.py b/GPy/inference/latent_function_inference/inferenceX.py index f68f17cb..a8ed2d09 100644 --- a/GPy/inference/latent_function_inference/inferenceX.py +++ b/GPy/inference/latent_function_inference/inferenceX.py @@ -45,17 +45,23 @@ class InferenceX(Model): super(InferenceX, self).__init__(name) self.likelihood = model.likelihood.copy() self.kern = model.kern.copy() - if model.kern.useGPU: - from ...models import SSGPLVM - if isinstance(model, SSGPLVM): - self.kern.GPU_SSRBF(True) - else: - self.kern.GPU(True) +# if model.kern.useGPU: +# from ...models import SSGPLVM +# if isinstance(model, SSGPLVM): +# self.kern.GPU_SSRBF(True) +# else: +# self.kern.GPU(True) from copy import deepcopy self.posterior = deepcopy(model.posterior) if hasattr(model, 'variational_prior'): self.uncertain_input = True - self.variational_prior = model.variational_prior.copy() + from ...models.ss_gplvm import IBPPrior + from ...models.ss_mrd import IBPPrior_SSMRD + if isinstance(model.variational_prior, IBPPrior) or isinstance(model.variational_prior, IBPPrior_SSMRD): + from ...core.parameterization.variational import SpikeAndSlabPrior + self.variational_prior = SpikeAndSlabPrior(pi=05,learnPi=False, group_spike=False) + else: + self.variational_prior = model.variational_prior.copy() else: self.uncertain_input = False if hasattr(model, 'inducing_inputs'): @@ -147,9 +153,9 @@ class InferenceX(Model): from ...core.parameterization.variational import SpikeAndSlabPrior if isinstance(self.variational_prior, SpikeAndSlabPrior): # Update Log-likelihood - KL_div = self.variational_prior.KL_divergence(self.X, N=self.Y.shape[0]) + KL_div = self.variational_prior.KL_divergence(self.X) # update for the KL divergence - self.variational_prior.update_gradients_KL(self.X, N=self.Y.shape[0]) + self.variational_prior.update_gradients_KL(self.X) else: # Update Log-likelihood KL_div = self.variational_prior.KL_divergence(self.X) diff --git a/GPy/kern/_src/rbf.py b/GPy/kern/_src/rbf.py index c6998370..73f2d0a4 100644 --- a/GPy/kern/_src/rbf.py +++ b/GPy/kern/_src/rbf.py @@ -20,7 +20,6 @@ class RBF(Stationary): _support_GPU = True def __init__(self, input_dim, variance=1., lengthscale=None, ARD=False, active_dims=None, name='rbf', useGPU=False): super(RBF, self).__init__(input_dim, variance, lengthscale, ARD, active_dims, name, useGPU=useGPU) - self.psicomp = PSICOMP_RBF() if self.useGPU: self.psicomp = PSICOMP_RBF_GPU() else: @@ -36,6 +35,7 @@ class RBF(Stationary): dc = super(RBF, self).__getstate__() if self.useGPU: dc['psicomp'] = PSICOMP_RBF() + dc['useGPU'] = False return dc def __setstate__(self, state): diff --git a/GPy/models/bayesian_gplvm_minibatch.py b/GPy/models/bayesian_gplvm_minibatch.py index 71f69eb2..7a7bb0e8 100644 --- a/GPy/models/bayesian_gplvm_minibatch.py +++ b/GPy/models/bayesian_gplvm_minibatch.py @@ -64,9 +64,6 @@ class BayesianGPLVMMiniBatch(SparseGPMiniBatch): self.logger.debug("creating inference_method var_dtc") inference_method = VarDTC(limit=1 if not missing_data else Y.shape[1]) - if kernel.useGPU and isinstance(inference_method, VarDTC_GPU): - kernel.psicomp.GPU_direct = True - super(BayesianGPLVMMiniBatch,self).__init__(X, Y, Z, kernel, likelihood=likelihood, name=name, inference_method=inference_method, normalizer=normalizer, diff --git a/GPy/plotting/matplot_dep/visualize.py b/GPy/plotting/matplot_dep/visualize.py index 6903c2d2..b17900db 100644 --- a/GPy/plotting/matplot_dep/visualize.py +++ b/GPy/plotting/matplot_dep/visualize.py @@ -451,7 +451,7 @@ class mocap_data_show(matplotlib_show): self.initialize_axes_modify() self.draw_vertices() self.initialize_axes() - self.finalize_axes_modify() + #self.finalize_axes_modify() self.draw_edges() self.axes.figure.canvas.draw() @@ -470,12 +470,20 @@ class mocap_data_show(matplotlib_show): self.line_handle[0].remove() def finalize_axes(self): - self.axes.set_xlim(self.x_lim) - self.axes.set_ylim(self.y_lim) - self.axes.set_zlim(self.z_lim) - self.axes.auto_scale_xyz([-1., 1.], [-1., 1.], [-1., 1.]) +# self.axes.set_xlim(self.x_lim) +# self.axes.set_ylim(self.y_lim) +# self.axes.set_zlim(self.z_lim) +# self.axes.auto_scale_xyz([-1., 1.], [-1., 1.], [-1., 1.]) -# self.axes.set_aspect('equal') + extents = np.array([getattr(self.axes, 'get_{}lim'.format(dim))() for dim in 'xyz']) + sz = extents[:,1] - extents[:,0] + centers = np.mean(extents, axis=1) + maxsize = max(abs(sz)) + r = maxsize/2 + for ctr, dim in zip(centers, 'xyz'): + getattr(self.axes, 'set_{}lim'.format(dim))(ctr - r, ctr + r) + +# self.axes.set_aspect('equal') # self.axes.autoscale(enable=False) def finalize_axes_modify(self): From efa65c864e19e4587e57866b929c0b83608b2c44 Mon Sep 17 00:00:00 2001 From: James Hensman Date: Thu, 16 Jul 2015 15:36:17 +0100 Subject: [PATCH 41/41] generalized the variatinoal Gaussian approximatino revisited code for any likelihood --- GPy/models/gp_var_gauss.py | 54 ++++++++++++++------------------------ 1 file changed, 19 insertions(+), 35 deletions(-) diff --git a/GPy/models/gp_var_gauss.py b/GPy/models/gp_var_gauss.py index cd688360..ccaab305 100644 --- a/GPy/models/gp_var_gauss.py +++ b/GPy/models/gp_var_gauss.py @@ -15,7 +15,7 @@ log_2_pi = np.log(2*np.pi) class GPVariationalGaussianApproximation(Model): """ - The Variational Gaussian Approximation revisited implementation for regression + The Variational Gaussian Approximation revisited @article{Opper:2009, title = {The Variational Gaussian Approximation Revisited}, @@ -25,44 +25,27 @@ class GPVariationalGaussianApproximation(Model): pages = {786--792}, } """ - def __init__(self, X, Y, kernel=None): + def __init__(self, X, Y, kernel, likelihood,Y_metadata=None): Model.__init__(self,'Variational GP classification') # accept the construction arguments self.X = ObsAr(X) - if kernel is None: - kernel = kern.RBF(X.shape[1]) + kern.White(X.shape[1], 0.01) - self.kern = kernel - self.link_parameter(self.kern) + self.Y = Y self.num_data, self.input_dim = self.X.shape + self.Y_metadata = Y_metadata - self.alpha = Param('alpha', np.zeros(self.num_data)) + self.kern = kernel + self.likelihood = likelihood + self.link_parameter(self.kern) + self.link_parameter(self.likelihood) + + self.alpha = Param('alpha', np.zeros((self.num_data,1))) # only one latent fn for now. self.beta = Param('beta', np.ones(self.num_data)) self.link_parameter(self.alpha) self.link_parameter(self.beta) - self.gh_x, self.gh_w = np.polynomial.hermite.hermgauss(20) - self.Ysign = np.where(Y==1, 1, -1).flatten() - def log_likelihood(self): - """ - Marginal log likelihood evaluation - """ return self._log_lik - def likelihood_quadrature(self, m, v): - """ - Perform Gauss-Hermite quadrature over the log of the likelihood, with a fixed weight - """ - # assume probit for now. - X = self.gh_x[None, :]*np.sqrt(2.*v[:, None]) + (m*self.Ysign)[:, None] - p = stats.norm.cdf(X) - N = stats.norm.pdf(X) - F = np.log(p).dot(self.gh_w) - NoverP = N/p - dF_dm = (NoverP*self.Ysign[:,None]).dot(self.gh_w) - dF_dv = -0.5*(NoverP**2 + NoverP*X).dot(self.gh_w) - return F, dF_dm, dF_dv - def parameters_changed(self): K = self.kern.K(self.X) m = K.dot(self.alpha) @@ -71,13 +54,14 @@ class GPVariationalGaussianApproximation(Model): A = np.eye(self.num_data) + BKB Ai, LA, _, Alogdet = pdinv(A) Sigma = np.diag(self.beta**-2) - Ai/self.beta[:, None]/self.beta[None, :] # posterior coavairance: need full matrix for gradients - var = np.diag(Sigma) + var = np.diag(Sigma).reshape(-1,1) - F, dF_dm, dF_dv = self.likelihood_quadrature(m, var) + F, dF_dm, dF_dv, dF_dthetaL = self.likelihood.variational_expectations(self.Y, m, var, Y_metadata=self.Y_metadata) + self.likelihood.gradient = dF_dthetaL.sum(1).sum(1) dF_da = np.dot(K, dF_dm) SigmaB = Sigma*self.beta - dF_db = -np.diag(Sigma.dot(np.diag(dF_dv)).dot(SigmaB))*2 - KL = 0.5*(Alogdet + np.trace(Ai) - self.num_data + m.dot(self.alpha)) + dF_db = -np.diag(Sigma.dot(np.diag(dF_dv.flatten())).dot(SigmaB))*2 + KL = 0.5*(Alogdet + np.trace(Ai) - self.num_data + np.sum(m*self.alpha)) dKL_da = m A_A2 = Ai - Ai.dot(Ai) dKL_db = np.diag(np.dot(KB.T, A_A2)) @@ -86,12 +70,12 @@ class GPVariationalGaussianApproximation(Model): self.beta.gradient = dF_db - dKL_db # K-gradients - dKL_dK = 0.5*(self.alpha[None, :]*self.alpha[:, None] + self.beta[:, None]*self.beta[None, :]*A_A2) + dKL_dK = 0.5*(self.alpha*self.alpha.T + self.beta[:, None]*self.beta[None, :]*A_A2) tmp = Ai*self.beta[:, None]/self.beta[None, :] - dF_dK = self.alpha[:, None]*dF_dm[None, :] + np.dot(tmp*dF_dv, tmp.T) + dF_dK = self.alpha*dF_dm.T + np.dot(tmp*dF_dv, tmp.T) self.kern.update_gradients_full(dF_dK - dKL_dK, self.X) - def predict(self, Xnew): + def _raw_predict(self, Xnew): """ Predict the function(s) at the new point(s) Xnew. @@ -105,4 +89,4 @@ class GPVariationalGaussianApproximation(Model): Kxx = self.kern.Kdiag(Xnew) var = Kxx - np.sum(WiKux*Kux, 0) - return 0.5*(1+erf(mu/np.sqrt(2.*(var+1)))) + return mu, var.reshape(-1,1)