mean_psf.py

import numpy as np

class PSF:
    def __init__(self, exposure, psf_value):
        self.exposure = exposure
        self.psf_value = psf_value

def get_psf(obs_id):
    psfs = {
        0 : PSF(exposure=np.ones_like(energies), psf_value=np.ones((len(energies), len(offsets)))),
        42 : PSF(exposure=np.ones_like(energies), psf_value=np.ones((len(energies), len(offsets)))),
        99: PSF(exposure=np.ones_like(energies), psf_value=np.ones((len(energies), len(offsets)))),
    }
    return psfs[obs_id]

        
def compute_mean_psf(obs_ids):

    psf0 = get_psf(obs_ids[0])
    mean_psf = PSF(
        exposure=np.zeros_like(psf0.exposure),
        psf_value=np.zeros_like(psf0.psf_value)
    )

    for obs_id in obs_ids:
        
        if obs_id is 'bad':
            continue
        
        psf = get_psf(obs_id)
    
    
    
    return mean_psf
        
energies = np.arange(10)
offsets = np.arange(10)

obs_id = [...]
print(compute_mean_psf(obs_ids=[0, 42, 99]))