Part working version of sympy covariance with new params version.

GPy/util/linalg.py

@@ -62,41 +62,41 @@ def force_F_ordered(A):
     print "why are your arrays not F order?"
     return np.asfortranarray(A)
 
+# def jitchol(A, maxtries=5):
+#     A = force_F_ordered_symmetric(A)
+#     L, info = lapack.dpotrf(A, lower=1)
+#     if info == 0:
+#         return L
+#     else:
+#         if maxtries==0:
+#             raise linalg.LinAlgError, "not positive definite, even with jitter."
+#         diagA = np.diag(A)
+#         if np.any(diagA <= 0.):
+#             raise linalg.LinAlgError, "not pd: non-positive diagonal elements"
+#         jitter = diagA.mean() * 1e-6
+
+#         return jitchol(A+np.eye(A.shape[0])*jitter, maxtries-1)
+
 def jitchol(A, maxtries=5):
-    A = force_F_ordered_symmetric(A)
-    L, info = lapack.dpotrf(A, lower=1)
-    if info == 0:
-        return L
-    else:
-        if maxtries==0:
-            raise linalg.LinAlgError, "not positive definite, even with jitter."
-        diagA = np.diag(A)
-        if np.any(diagA <= 0.):
-            raise linalg.LinAlgError, "not pd: non-positive diagonal elements"
-        jitter = diagA.mean() * 1e-6
+   A = np.ascontiguousarray(A)
+   L, info = lapack.dpotrf(A, lower=1)
+   if info == 0:
+       return L
+   else:
+       diagA = np.diag(A)
+       if np.any(diagA <= 0.):
+           raise linalg.LinAlgError, "not pd: non-positive diagonal elements"
+       jitter = diagA.mean() * 1e-6
+       while maxtries > 0 and np.isfinite(jitter):
+           print 'Warning: adding jitter of {:.10e}'.format(jitter)
+           try:
+               return linalg.cholesky(A + np.eye(A.shape[0]).T * jitter, lower=True)
+           except:
+               jitter *= 10
+           finally:
+               maxtries -= 1
+       raise linalg.LinAlgError, "not positive definite, even with jitter."
 
-        return jitchol(A+np.eye(A.shape[0])*jitter, maxtries-1)
-
-#def jitchol(A, maxtries=5):
-#    A = np.ascontiguousarray(A)
-#    L, info = lapack.dpotrf(A, lower=1)
-#    if info == 0:
-#        return L
-#    else:
-#        diagA = np.diag(A)
-#        if np.any(diagA <= 0.):
-#            raise linalg.LinAlgError, "not pd: non-positive diagonal elements"
-#        jitter = diagA.mean() * 1e-6
-#        while maxtries > 0 and np.isfinite(jitter):
-#            print 'Warning: adding jitter of {:.10e}'.format(jitter)
-#            try:
-#                return linalg.cholesky(A + np.eye(A.shape[0]).T * jitter, lower=True)
-#            except:
-#                jitter *= 10
-#            finally:
-#                maxtries -= 1
-#        raise linalg.LinAlgError, "not positive definite, even with jitter."
-#