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authoroysstu2018-09-16 16:50:01 +0200
committeroysstu2018-09-16 16:50:01 +0200
commitc70b126a578e47ee1fe0e0f3093c7e7dfbfaf0d2 (patch)
tree1c6c8865e8fc69ccafc5fd7003d45a1ac8745340
parent80804e613eab910dcdeac94c060728210164877f (diff)
downloadaur-c70b126a578e47ee1fe0e0f3093c7e7dfbfaf0d2.tar.gz
Update to v1.9.5
-rw-r--r--cython-v1.9.5.patch37
1 files changed, 37 insertions, 0 deletions
diff --git a/cython-v1.9.5.patch b/cython-v1.9.5.patch
new file mode 100644
index 00000000000..2693eedcf9d
--- /dev/null
+++ b/cython-v1.9.5.patch
@@ -0,0 +1,37 @@
+diff -ura src/GPy-1.9.5/GPy/models/state_space_cython.pyx src/GPy-1.9.5/GPy/models/state_space_cython.pyx
+--- src/GPy-1.9.5/GPy/models/state_space_cython.pyx 2018-09-02 23:50:17.000000000 +0200
++++ src/GPy-1.9.5/GPy/models/state_space_cython.pyx 2018-09-16 16:16:08.000000000 +0200
+@@ -484,7 +484,7 @@
+ if matrix_index in self.Q_square_root_dict:
+ square_root = self.Q_square_root_dict[matrix_index]
+ else:
+- if matrix_index not in self.Q_svd_dict
++ if matrix_index not in self.Q_svd_dict:
+ U,S,Vh = sp.linalg.svd( self.Qs[:,:, matrix_index],
+ full_matrices=False, compute_uv=True,
+ overwrite_a=False, check_finite=False)
+@@ -514,7 +514,7 @@
+ if matrix_index in self.Q_inverse_dict:
+ Q_inverse = self.Q_inverse_dict[matrix_index]
+ else:
+- if matrix_index not in self.Q_svd_dict
++ if matrix_index not in self.Q_svd_dict:
+ U,S,Vh = sp.linalg.svd( self.Qs[:,:, matrix_index],
+ full_matrices=False, compute_uv=True,
+ overwrite_a=False, check_finite=False)
+@@ -522,7 +522,7 @@
+ else:
+ U,S,Vh = self.Q_svd_dict[matrix_index]
+
+- Q_inverse = Q_inverse = np.dot( Vh.T * ( 1.0/(S + jitter)) , U.T )
++ Q_inverse = Q_inverse = np.dot( Vh.T * ( 1.0/(S + jitter)) , U.T )
+ self.Q_inverse_dict[matrix_index] = Q_inverse
+
+ return Q_inverse
+@@ -998,4 +998,4 @@
+ M[k+1,:,:] = m_upd # separate mean value for each time series
+ P[k+1,:,:] = P_upd[0]
+
+- return (M, P, log_likelihood, grad_log_likelihood, p_dynamic_callables.reset(False))
+\ No newline at end of file
++ return (M, P, log_likelihood, grad_log_likelihood, p_dynamic_callables.reset(False))