xenonnt / appletree Goto Github PK

Not sure why but the cut acceptance is not implemented in the appletree default ER model.

Sometimes the constraining power is from literature, such as:

1. Low-energy (0.7-74 keV) nuclear recoil calibration of the LUX dark matter experiment using D-D neutron scattering kinematics
2. Low-Energy Physics Reach of Xenon Detectors for Nuclear-Recoil-Based Dark Matter and Neutrino Experiments

We need more instructions about the standard and user-specified workflow of appletree. Put them in notebooks folder.

In neutron calibration, multi-scatter S2s might be merged together. We need to recurrent the workflow in BBF.

Of course, for a public repo, this is definitely needed.

We should add a helpful document including a tutorial, workflow, and configuration guide.

In https://github.com/XENONnT/appletree/blob/master/appletree/plugin.py#L80 and https://github.com/XENONnT/appletree/blob/master/appletree/component.py#L469 there are no hints showed to the user that there is previously a plugin/component with the same name.

To stop reviewdog complaining like: #14 (review)

Function in GOFevaluation provides a way to calculate binning of equiprobable_histogram, but the reference_sample is equally weighted.

For consistency between data selection and modeling, we need to be sure that the ROI(cs1, cs2, x, y, z) selections are the same.

Current test coverage is only ~80%(look at Pull Request Test Coverage Report for more information), we should add more tests on all the features.

When loading the config file, sometimes it loads NoneType and it's hard to know which file failed.
``File` ~/appletree/appletree/utils.py:88, in load_json(file_name)
85 @export
86 def load_json(file_name: str):
87 """Load data from json file."""
---> 88 with open(get_file_path(file_name), 'r') as file:
89 data = json.load(file)
90 return data

TypeError: expected str, bytes or os.PathLike object, not NoneType
``

My temporary fix is to make it print all names in
`@export
class Map(Config):
"""Map is a special config which takes input file"""

def build(self):
    """Cache the map to jnp.array"""

    
    if self.name in _cached_configs:
        print('want to get:',self.name)
        file_path = _cached_configs[self.name]
        
    else:
        file_path = get_file_path(self.get_default())
        _cached_configs.update({self.name: file_path})

`
But there might be better ways to print what didn't load.

NEST "is an unprecedentedly comprehensive, accurate, and precise simulation of the excitation, ionization, and corresponding scintillation and electroluminescence processes in liquid noble elements". For purpose of comparison, we might want to add such a NEST model in the simulation.

We should track the simulation results with the version of the package, configuration files, and input files(maps, corrections, and calibration data). Maybe follow the scenario in strax to use the lineage and hash.