 import argparse
import os
import sys
import h5py
import numpy as np
from sirf.Engine import get_engine
from sirf.IO import load_acquisition_data, save\_acquisition\_data
from sirf.PhysicsModel import create_physics_model
from sirf.AcquisitionModel import create\_acquisition\_model
from sirf.Optimisation import create\_conjugate\_gradient\_optimiser
from sirf.Trajectory import create\_trajectory
from sirf.Preprocessing import create\_preprocessor

def define\_symmetric\_operator(kspace):
"""
Define a symmetrical operator for cg-optimisation
"""
return kspace

def conjugate\_gradient(kspace, sensitivity\_maps, acquisition\_model, physics\_model, max\_iter, tol):
"""
Perform the Conjugate Gradient method
"""
cg\_optimiser = create\_conjugate\_gradient\_optimiser(define\_symmetric\_operator(kspace), max\_iter, tol)
return cg\_optimiser.optimise(sensitivity\_maps, acquisition\_model, physics\_model)

def main():
parser = argparse.ArgumentParser(description='Iterative reconstruction with radial phase encoding (RPE) data using the SIRF library.')

parser.add\_argument('--raw\_data\_file', type=str, required=True,
help='Path to the raw data file')

parser.add\_argument('--data\_path', type=str, required=True,
help='Path to data files')

parser.add\_argument('--output\_file', type=str, required=True,
help='Path to output file for simulated data')

parser.add\_argument('--engine', type=str, choices=['reconengine1', 'reconengine2'], required=True,
help='Reconstruction engine to use')

parser.add\_argument('--run\_recon', action='store\_true',
help='Run the reconstruction if non-cartesian code was compiled')

parser.add\_argument('--trajectory', type=str, choices=['cartesian', 'radial', 'goldenangle', 'grpe'], default='radial',
help='Trajectory type (cartesian, radial, goldenangle or grpe)')

parser.add\_argument('--show\_plots', action='store\_true',
help='Show plots')

args = parser.parse\_args()

try:
engine\_module = get\_engine(args.engine)
except Exception as e:
print(f'Error: Unable to import engine module: {e}')
sys.exit(1)

try:
acquisition\_data = load\_acquisition\_data(os.path.join(args.data\_path, 'acquisition_data.h5'))
except Exception as e:
print(f'Error: Unable to load acquisition data: {e}')
sys.exit(1)

preprocessor = create\_preprocessor()
preprocessor.preprocess(acquisition\_data)

trajectory = create\_trajectory(args.trajectory)
trajectory.set\_kspace(acquisition\_data.get\_kspace())

sorted\_kspace = trajectory.sort\_kspace()

kspace = sorted\_kspace.get\_kspace\_data()

if args.engine == 'reconengine1':
physics\_model = engine\_module.PhysicsModel1()
acquisition\_model = engine\_module.AcquisitionModel1()
elif args.engine == 'reconengine2':
physics\_model = engine\_module.PhysicsModel2()
acquisition\_model = engine\_module.AcquisitionModel2()

sensitivity\_maps = conjugate\_gradient(kspace, acquisition\_data.get\_sensitivity\_maps(), acquisition\_model, physics\_model, 50, 1e-5)

if args.run\_recon:
recon\_data = engine\_module.create\_reconstruction\_data(sensitivity\_maps, acquisition\_data)
save\_acquisition\_data(os.path.join(args.output\_file), recon\_data)

if args.show\_plots:
# Show plots
pass

if __name__ == '__main__':
main()