[srean]

>For high abstraction and friendliness, C++ doesn't do nearly as nice of a job as MATLAB or Python in exposing high-level scientific computing operations.

I think you responded to it yourself in the next paragraph.

While not quite the same as using MATLAB or Numpy; with Eigen, Blitz++ and Armadillo you can come really close syntactically. You do have to suffer through the compilation process but it comes with computational benefits. Numpy and its ilk are adversely affected by the limitation of their vectorization paradigm, some more, some less. This style creates needless copies, unnecessary and overly pessimistic loops. These cost performance. Eigen/Blitz++/Armadillo style libraries do not suffer from this problem. A common Pythonic way to recover from these deficiencies of Numpy is to use Cython (and numexpr although it has a very narrow scope). However, to see speedups in these tight numerical loops with Cython one really has to do manual indexing, write at a low level, not so for Eigen/Armadillo/Blitz++.

This, although very limited in scope, is a concrete example that shows that you can write at a higher level in C++ without incurring performance hits.