Performance and stability improvements to wcs.all_world2pix

Significant improvements to the performance (typically 1000-2000 times faster) and stability of `wcs.all_world2pix` function. The used algorithm is a completely vectorized implementation of the method of consecutive approximations (fixed point iterations). While this method is a low-order method, it is more than adequate for geometric distortions that are typical in astrophysical images (smooth, slowly varying polynomials). ~~The method is somewhat similar to the existing `HSTWCS.all_sky2pix`, though~~ The
choice of the function, initial approximation, and implementation, makes the method proposed here to converge in half of the iterations of `HSTWCS.all_sky2pix`.

Compared to the original implementation of `all_world2pix`, this implementation does not require users to have SciPy installed in order to run.

While there is a check to see if WCS contains higher-order distortions (and return the exact solution if it does not), the method itself does not *require* this check and will converge to the exact solution after one iteration if WCS does not contain higher order distortions. This check is mostly for performance purposes to avoid unnecessary iterative solution for images that do not contain distortions (and pix->sky requires only WCS-based, i.e., CD-only transformations).

The proposed replacement for the current implementation of `all_world2pix` avoids unnecessary use of `wcs_world2pix` and `all_pix2world` such as `wcs_world2pix(all_pix2world(pix))` by replacing this with `pix2foc`. This avoids unnecessary CD-matrix based transformation CD(CD^{-1})=I which in itself results in about 50% performance improvement over `wcs_world2pix(all_pix2world(pix))` and likely 25% over `all_pix2world` alone.

The function has additional code to check for *divergence* condition (as opposite to *slow convergence*) when consecutive approximations *diverge*. This can happen when the pixel coordinates are *far* away from the reference pixel (distortions are "severely" extrapolated), or for poorly-defined geometric distortions (at least for this numerical method).

A "new and improved" :smiley: `NoConvergence` exception has attributes that allows users to retrieve best solution reached by the function, and indices of *slowly converging* solutions (points) that *did not converge* in the specified maximum number of iterations as well as indices of *diverging* solutions (likely an indication of poorly described distortions or very large distortions).

Finally, the new test function `test_all_world2pix_direct` (proposed as a replacement to the old test) provides a much more improved (versatile) and *thorough* test of the `all_world2pix` function.

These improvements address the issues raised in #1977, https://github.com/scipy/scipy/issues/3227 that plagued `all_world2pix`, and #2294 (in addition to performance improvements).