shot-by-shot energy and/or masks

[tjlane]

Here's what needs to happen. There are two options.

OPTION 1: Python parallel
(1) Remove xray.Shotset._implicit_interpolation inner loop over shots -- just does one shot at a time
(2) Parallelize xray.Shotset._implicit_interpolation at that level

Benefits: easy to code
Downsides: will use a lot of memory
Challenges: need to parallelize a class method robustly

OPTION 2: OMP parallel
(1) If many energies are passed, compute detector intersections inside loop over shot intensities (https://github.com/tjlane/odin/blob/master/src/python/xray/xray.py#L1342)
(2) Parallize scipy.ndimage.map_coordiantes w/OMP and build it in odin
(3) Benchmark the detector intersection computation, and if rate-limiting, parallelize

Benefits: higher-performance final product
Downsides: more coding
Challenges: getting scipy code we call parallel/wrapped

[tjlane]

Going with OPTION 2, above, combined with the ability for shotsets to contain a list of detector objects.

So, this gives me a significant amount to do:
(1) Rip out the scipy interpolation algo and OMP it
(2) Extend xray.Shotset to hold a list of xray.Detectors, and use them in all calcs
(3) Amend xray.Shotset._implicit_interpolation to use the new code
(4) Test the speed of computing ray intersections in xray.Detector` and parallelize if very slow