Turn run_recipes into an importable class

[JenniferKarr]

Turned the script format of run_recipes in to an importable class, in preparation for allowing separate directories for different types of simulations (ESO, AIT).

The running of the simulations is unchanged but there is a fairly major reorganization of the code.

run_recipes.py has the same calling syntax as before, but now acts as a wrapper for the class in runRecipes.py.

The command line parameters are now stored in a dictionary in runRecipes.params, rather than a series of individual variables.

updateHeaders has been incorporated into the main routine.

The option --calibFile will write the calibration dictionary to a YAML file in the same form as the input YAML.

The DIT field in thex output file names has been removed as unneeded.

The validation has been updated to include the list of filter and ndfilter names.

There are now methods
parseCommandLine(args) - parse the command line options

loadYAML() - read in the YAML file and filter
   _load_yaml - load the YAML
   _filter_yaml - filter the dictionary

validateYAML() - validate the keywords

calcDark(props) - given a dictionary, determine the dark (if any) that is needed

calcSkyFlat(props) - given a dictionary, determine the sky flat (if any) that is needed

calcLampFlat(props) - given a dictionary, determine the lamp flat (if any) that is needed

calculateCalibs - generate a dictionary, in the same format as read from the YAML file, for flats and darks

generateFilename(dateobs,doCatg,dit,prefix) - generate a filename for the output file

dumpCalibsToFile(filename) - write the calibration dictionary to a YAML file (which could be used as input to run_recipes)

updateHeaders - update the headers for generate files

runSimulations(recipes) - wrapper to call the main _run method for the YAML file

runCalibraitons(recipes) - wrapper to call the main _run method for the calibrations

_run(recipes) - run simulations for the set of recipes

[hugobuddel]

Great!