Re: Issue 3615 in sympy: Test failure with numpy 1.7.0

2013-03-08 Thread sympy
Updates: Status: Fixed Comment #7 on issue 3615 by julien.r...@gmail.com: Test failure with numpy 1.7.0 http://code.google.com/p/sympy/issues/detail?id=3615 (No comment was entered for this change.) -- You received this message because this project is configured to send all issue

Re: Issue 3615 in sympy: Test failure with numpy 1.7.0

2013-02-27 Thread sympy
Updates: Status: Started Comment #6 on issue 3615 by asmeu...@gmail.com: Test failure with numpy 1.7.0 http://code.google.com/p/sympy/issues/detail?id=3615 We just needed to bump up our Matrix.__array_priority__, which was set to 10. See https://github.com/sympy/sympy/pull/1846.

Re: Issue 3615 in sympy: Test failure with numpy 1.7.0

2013-02-19 Thread sympy
Comment #4 on issue 3615 by asmeu...@gmail.com: Test failure with numpy 1.7.0 http://code.google.com/p/sympy/issues/detail?id=3615 See https://github.com/numpy/numpy/issues/3004. -- You received this message because this project is configured to send all issue notifications to this

Re: Issue 3615 in sympy: Test failure with numpy 1.7.0

2013-02-17 Thread sympy
Updates: Summary: Test failure with numpy 1.7.0 Comment #1 on issue 3615 by asmeu...@gmail.com: Test failure with numpy 1.7.0 http://code.google.com/p/sympy/issues/detail?id=3615 It's not Python 3 but rather NumPy 1.7.0. I just verified the same error in Python 2 with the 1.7.0

Re: Issue 3615 in sympy: Test failure with numpy 1.7.0

2013-02-17 Thread sympy
Comment #2 on issue 3615 by asmeu...@gmail.com: Test failure with numpy 1.7.0 http://code.google.com/p/sympy/issues/detail?id=3615 numpy.matrix.__add__ must be smarter. -- You received this message because this project is configured to send all issue notifications to this address. You

Re: Issue 3615 in sympy: Test failure with numpy 1.7.0

2013-02-17 Thread sympy
Comment #3 on issue 3615 by asmeu...@gmail.com: Test failure with numpy 1.7.0 http://code.google.com/p/sympy/issues/detail?id=3615 There's another test that tests the same thing with multiplication, and it works. So probably either way this is a numpy bug, since it should be consistant.