From 5d1875ec4452b5b46f2453bb6ef82c7031af9a64 Mon Sep 17 00:00:00 2001
From: James Hensman <james.hensman@gmail.com>
Date: Tue, 5 May 2015 14:13:38 +0100
Subject: [PATCH 1/5] 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 <stddef.h>
 #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<typename T>
 void __Pyx_call_destructor(T* x) {
     x->~T();
 }
-template<typename T>
-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 = ((<char*>&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 = ((<char*>&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 = <Py_ssize_t*>stdlib.malloc(sizeof(Py_ssize_t) * <size_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 = <Py_ssize_t*>stdlib.malloc(sizeof(Py_ssize_t) * <size_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 = <Py_ssize_t*>stdlib.malloc(sizeof(Py_ssize_t) * <size_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 = <Py_ssize_t*>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 = <Py_ssize_t*>PyArray_STRIDES(self)
  *                 info.shape = <Py_ssize_t*>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 = <Py_ssize_t*>PyArray_STRIDES(self)
  *                 info.shape = <Py_ssize_t*>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 = <Py_ssize_t*>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"
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-      /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":273
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-      /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":274
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-      /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":275
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-      /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":276
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-      /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":277
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-    /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":280
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-    /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":281
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-    /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":283
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-    /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":289
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-    /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":981
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  * 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]
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+  __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;}
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-  __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;}
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@@ -4567,7 +4539,7 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void)
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  * 
  * 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
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  */
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@@ -4579,8 +4551,8 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void)
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  * 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]
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   __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;}
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@@ -4609,7 +4581,7 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void)
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-  /* "../../../../anaconda/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":979
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@@ -4625,6 +4597,7 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void)
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+      Py_DECREF(__pyx_d); __pyx_d = 0;
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     Py_DECREF(__pyx_m); __pyx_m = 0;
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@@ -4639,7 +4612,7 @@ PyMODINIT_FUNC PyInit_choleskies_cython(void)
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 }
 
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 static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname) {
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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 <james.hensman@gmail.com>
Date: Tue, 5 May 2015 14:29:07 +0100
Subject: [PATCH 2/5] 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 14043be0ce46cc92868e7bee6864aab7d9051223 Mon Sep 17 00:00:00 2001
From: James Hensman <james.hensman@gmail.com>
Date: Thu, 14 May 2015 16:49:11 +0100
Subject: [PATCH 3/5] 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 2249ec06a597edeecf8c0709e354ec9af5c2a91e Mon Sep 17 00:00:00 2001
From: James Hensman <james.hensman@gmail.com>
Date: Fri, 15 May 2015 08:10:34 +0100
Subject: [PATCH 4/5] 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<Q; q++){
+    dist = X[nQ+q]-X2[mQ+q];
+    grad[q] += tmp[nm]*dist*dist;
+  }
+}
+} //lengthscale_grads
+
 
 void _lengthscale_grads(int N, int M, int Q, double* tmp, double* X, double* X2, double* grad){
 int n,m,q;
@@ -34,3 +50,5 @@ for(q=0; q<Q; q++){
 
 
 
+
+

From 77093a304caad25559d918fe00a81795a3dbbaa6 Mon Sep 17 00:00:00 2001
From: James Hensman <james.hensman@gmail.com>
Date: Fri, 15 May 2015 08:59:19 +0100
Subject: [PATCH 5/5] 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