Testing against NumPy/SciPy sane version pairs
This doesn't completely answer your question, but I think the policy of scipy release management since 0.11 or earlier has been to support all of the numpy versions from 1.5.1 up to the numpy version in development at the time of the scipy release.
Testing against NumPy/SciPy includes testing against several versions of them, since there is the need to support all versions since Numpy 1.6 and Scipy 0.11.
Testing all combinations would explode the build matrix in continuous integration (like travis-ci). I've searched the SciPy homepage for notes about version compatibility or sane combinations, but have not found something useful.
So my question is how to safely reduce the amount of combinations, while maintaining maximum testing compliance.
Is it possible to find all combinations in the wild? Or are there certain dependencies between Scipy and Numpy?