Thanks to the input of Nathann the number of failed doctests was greatly reduced.
linear_programming.rst
This seems to be just another just-as-good solution. Probably, the doctest should be changed to allow alternative solutions?
sage -t -long -force_lib "devel/sage/doc/en/thematic_tutorials/linear_programming.rst"
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File "/home/malb/Sage/current/devel/sage/doc/en/thematic_tutorials/linear_programming.rst", line 366:
sage: [e for e,b in matching.iteritems() if b == 1]
Expected:
[(0, 1), (6, 9), (2, 7), (3, 4), (5, 8)]
Got:
[(1, 6), (0, 4), (2, 3), (5, 8), (7, 9)]
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digraph.py
Is this worrisome?
sage -t -long -force_lib "devel/sage/sage/graphs/digraph.py"
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File "/home/malb/Sage/current/devel/sage/sage/graphs/digraph.py", line 1539:
sage: x == y
Expected:
True
Got:
False
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mip.pyx
These are purely cosmetic.
sage -t -long -force_lib "devel/sage/sage/numerical/mip.pyx"
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File "/home/malb/Sage/current/devel/sage/sage/numerical/mip.pyx", line 648:
sage: p.solve()
Expected:
0.0
Got:
-0.0
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File "/home/malb/Sage/current/devel/sage/sage/numerical/mip.pyx", line 1216:
sage: p.get_backend()
Expected:
<sage.numerical.backends.glpk_backend.GLPKBackend object ...>
Got:
SCIP Constraint Integer Program "" ( maximization, 0 variables, 0 constraints )
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File "/home/malb/Sage/current/devel/sage/sage/numerical/mip.pyx", line 365:
sage: p.show()
Expected:
Maximization:
Hey[1] +Hey[2]
Constraints:
Constraint_1: -3.0 Hey[1] +2.0 Hey[2] <= 2.0
Variables:
Hey[1] is a continuous variable (min=0.0, max=+oo)
Hey[2] is a continuous variable (min=0.0, max=+oo)
Got:
Maximization:
x_0 +x_1
Constraints:
Constraint_1: -3.0 x_0 +2.0 x_1 <= 2.0
Variables:
x_0 is a continuous variable (min=0.0, max=+oo)
x_1 is a continuous variable (min=0.0, max=+oo)
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