Add sqrt member to AffineScalarFunc to make numpy.linalg.norm work

[karlwessel]

This is my own try at fixing issue #121.

It works by adding sqrt as a member function to AffineScalarFunc so that numpy knows how to calculate the square root of it.

This also makes some other numpy methods work like numpy.sqrt.

[pkienzle]

The method used here (adding sqrt to the class) will work for many (all?) of the functions in umath, so for example np.sin(ufloat) would return umath.sin(ufloat). Any interest in extending this patch to include all these functions?

The attribute would be needed for both Variable and AffineScalarFunc.

Some methods will need different names, such as arcsin instead of asin.

[karlwessel]

The method used here (adding sqrt to the class) will work for many (all?) of the functions in umath, so for example np.sin(ufloat) would return umath.sin(ufloat). Any interest in extending this patch to include all these functions?

The attribute would be needed for both Variable and AffineScalarFunc.

Some methods will need different names, such as arcsin instead of asin.

During implementation of the patch I already did that for exp but removed it in the end to keep the PR on point (which is just fixing issue #121).

I think once this PR is merged and has proven to work for some time, one could implement your suggestion in a separate PR.

[AndrewAnnex]

I can see that some time has past since this pr was last updated, and I just ran into this issue (plus the norm one) when attempting to use uncertainties with statsmodels. Are the failed checks related to an incomplete implementation? If this works as-is I can make progress on my own work by just monkey-patching

[AndrewAnnex]

I also see an issue where numpy needs an implementation of the conjugate method as the default in numpy is to use the Frobenius norm, although this is really not my area