Llr optimizer initial

Hi Sebastian,

This is my latest pull request, which includes the initial code for the LLR Optimizer analysis. I have also updated Steve's template.py code, by taking the approach you suggested-grab his template.py from his repo and incorporate all the suggestions that I commented on myself. I also have tried to upload all data and input files, so if there are any missing, please let me know! The only thing really missing from the optimizer analysis code right now is the implementation of a few additional systematics, as well as adding the priors on the parameters that we do not wish to constrain.
This function is a little odd, as it mixes two tasks, that have to do with different things: getting the fixed values for the constant parameters, and getting a list of non-fixed parameters. Instead I would propose to have the first task accomplished by the function in line 53, which can take an extra flag (`fixed_only`), to only give you the fiducial values of the fixed parameters. Then this function for the non-fixed parameters becomes much easier:
```
def get_free_params(params, hierarchy='normal'):
    freeparams = {}
    for key, value in select_hierarchy(params, hiearchy):
        freeparams[key] = value
    return freeparams
```