import sys
import numpy as np
from sirf.STIR import *
from sirf_exercises import cd_to_working_dir

def cg_reconstruction(raw_data_file, path_to_data_files, output_file, engine, non_cartesian, trajectory_type, show_plots):
    # Import necessary engine module
    if engine == 'STIR':
        from sirf.STIR import Reconstruction
    elif engine == 'Gadgetron':
        from sirf.Gadgetron import Reconstruction
    else:
        print('Invalid engine option. Please choose either STIR or Gadgetron.')
        sys.exit(1)
    
    # Process command-line options
    # Define symmetrical operator for cg-optimisation
    
    def cg_method():
        # Compute coil sensitivity maps
        # Set up acquisition model
        # Perform backward projection
        # Implement iterative reconstruction
    
    def main():
        # Locate k-space raw data file
        # Read acquisition data from HDF file
        # Pre-process acquisition data
        # Set trajectory
        # Sort processed acquisition data
        # Perform reconstruction if relevant option is set
    
    try:
        main()
    except error as err:
        print(f'Error occurred: {err}')

if __name__ == '__main__':
    raw_data_file = ''
    path_to_data_files = ''
    output_file = ''
    engine = ''
    non_cartesian = False
    trajectory_type = ''
    show_plots = False
    
    cg_reconstruction(raw_data_file, path_to_data_files, output_file, engine, non_cartesian, trajectory_type, show_plots)