read_save.py

import h5py
import numpy as  np
import pandas as pd
import astropy.units as u
from astropy.table import QTable
from astropy.time import Time
from astropy.coordinates import SkyCoord

def save_sim(iloc, path_to_save, my_own_model, pyLIMA_parameters, event_params):
    print('Saving Simulation...')
    # Save to an HDF5 file with specified names
    with h5py.File(path_to_save + 'Event_' + str(iloc) + '.h5', 'w') as file:
        # Save array with a specified name
        file.create_dataset('Data', data=np.array([iloc, my_own_model.origin[0]], dtype='S'))
        # Save dictionary with a specified name
        dict_group = file.create_group('pyLIMA_parameters')
        for key, value in pyLIMA_parameters.items():
            dict_group.attrs[key] = value
            
        dict_group_tril = file.create_group('TRILEGAL_params')
        for key, value in event_params.items():
            dict_group_tril.attrs[key] = value

        # Save table with a specified name
        for telo in my_own_model.event.telescopes:
            table = telo.lightcurve
            table_group = file.create_group(telo.name)
            for col in table.colnames:
                table_group.create_dataset(col, data=table[col])
    print('File saved:',path_to_save + 'Event_' + str(iloc) + '.h5' )


def read_data(path_model):
    # Open the HDF5 file and load data using specified names
    with h5py.File(path_model, 'r') as file:
        # Load array with string with info of dataset using its name
        info_dataset = file['Data'][:]
        info_dataset = [ file['Data'][:][0].decode('UTF-8'),
                        [file['Data'][:][1].decode('UTF-8'), [0, 0]]]
        # Dictionary using its name
        pyLIMA_parameters = {key: file['pyLIMA_parameters'].attrs[key] for key in file['pyLIMA_parameters'].attrs}
        # Load table using its name
        bands = {}
        for band in ("u", "g", "r", "i", "z", "y"):
            loaded_table = QTable()
            for col in file[band]:
                loaded_table[col] = file[band][col][:]
            bands[band] = loaded_table
        return info_dataset, pyLIMA_parameters, bands