Fix up for modern Nim, add comment about beamline

[Vindaar]

Makes it compile on modern Nim and comments on the LLNL beamline. In addition one can now hand a suffix that will be added to the axion image CSV and plot files.

Also makes it generate a CSV file for the differential flux.

Finally, the multithreading is taken out for now, because on modern Nim it seems to cause a segfault. The code is fast enough for the required statistics for the time being and I don't feel like debugging the issue.

edit:
Also updates the LLNL reflectivity generation tool to support generating the data in the ranges as required by REST.

To generate the correct file run:

./llnl_layer_reflectivity \
    --numEnergy 500 \
    --angleMax 9.0.° \
    --numAngle 901 \
    --outfile llnl_layer_reflectivities_rest.h5 \
    --outpath /path/to/foo

The HDF5 file then needs to be converted to the raw binary format. This can be done with the following snippet utilizing nio (https://github.com/c-blake/nio):

import nimhdf5, strutils, sequtils, arraymancer
import nio
const path = "/home/basti/org/resources/llnl_layer_reflectivities_rest.h5"
let h5f = H5open(path, "r")
h5f.visit_file()
let grp = h5f["/".grp_str]
for dset in grp:
  echo dset.name, " of shape ", dset.shape
  if "Reflectivity" in dset.name:
    let data = toTensor(h5f[dset.name, float]).asType(float32) # convert to float32
      .reshape(dset.shape)
      .transpose # transpose our data
    echo data.shape
    let dataS = data.toSeq2D
    echo dataS.shape
    # convert to seq[array]
    var dataA = newSeq[array[901, float32]](500)
    for i in 0 ..< dataS.len:
      copyMem(dataA[i][0].addr, dataS[i][0].addr, 901 * sizeof(float32))

    let name = dset.name
    dataA.save "/tmp/" & name
    
discard h5f.close()  

(Adjust the PATH as needed of course). I don't add this code to this repostiory, as it is a bit out of scope and this is just one possible implementation. I don't expect anyone else to actually use this approach anyway.

IMPORTANT: While implementing multilayer reflectivity coatings in xrayAttenuation I've realized that I've been using DarpanX wrong. The d_min and d_max values need to be handed to it in Ångström instead of nano meters. Also their code is a mess, so I'm going to finish the multilayer code and then we compute it ourselves.