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24 lines
1.4 KiB
Diff
24 lines
1.4 KiB
Diff
diff -up src/sage/numerical/backends/cvxopt_backend.pyx.orig src/sage/numerical/backends/cvxopt_backend.pyx
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--- src/sage/numerical/backends/cvxopt_backend.pyx.orig 2021-05-09 16:00:11.000000000 -0600
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+++ src/sage/numerical/backends/cvxopt_backend.pyx 2021-05-28 12:05:47.551650940 -0600
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@@ -550,7 +550,7 @@ cdef class CVXOPTBackend(GenericBackend)
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self.answer = solvers.lp(c,G,h)
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#possible outcomes
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- if self.answer['status'] == 'optimized':
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+ if self.answer['status'] in ['optimized', 'optimal']:
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pass
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elif self.answer['status'] == 'primal infeasible':
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raise MIPSolverException("CVXOPT: primal infeasible")
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diff -up src/sage/numerical/backends/cvxopt_sdp_backend.pyx.orig src/sage/numerical/backends/cvxopt_sdp_backend.pyx
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--- src/sage/numerical/backends/cvxopt_sdp_backend.pyx.orig 2021-05-09 16:00:11.000000000 -0600
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+++ src/sage/numerical/backends/cvxopt_sdp_backend.pyx 2021-05-28 12:05:47.552650940 -0600
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@@ -150,7 +150,7 @@ cdef class CVXOPTSDPBackend(MatrixSDPBac
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self.answer = solvers.sdp(c,Gs=G_matrix,hs=h_matrix)
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#possible outcomes
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- if self.answer['status'] == 'optimized':
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+ if self.answer['status'] in ['optimized', 'optimal']:
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pass
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elif self.answer['status'] == 'primal infeasible':
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raise SDPSolverException("CVXOPT: primal infeasible")
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