 Here is a Python script that follows your instructions. I've assumed that the reconstruction engine is imported from the `sirf.engines` module. Please replace `MyReconstructionEngine` with the actual engine class you want to use.

```python
import argparse
import sys
import numpy as np
from sirf.engines import MyReconstructionEngine
from sirf.processors import TruncateToCylinderProcessor
from sirf.data import ImageData, AcquisitionData, NiftiImageData
from sirf.objectives import PoissonLogLikelihoodWithLinearModelForMeanAndProjData, TestSTIRObjectiveFunction

def truncate_to_cylinder(image, diameter):
    processor = TruncateToCylinderProcessor(diameter)
    return processor.process(image)

def perform_steepest_ascent(data, engine, objective_function, num_steps, locally_optimal, verbose, plot):
    try:
        initial_image = NiftiImageData.create_from_3D_image(np.zeros(data.data_type.shape))
        model = engine.create_from_3D_image(initial_image)

        acquisition_data = AcquisitionData.from_acquisition_data(data)
        acquisition_data.set_objective_function(objective_function)
        objective_function.set_acquisition_data(acquisition_data)

        filter_ = ImageDataProcessor(truncate_to_cylinder)
        filtered_data = filter_.process(data)

        filtered_acquisition_data = AcquisitionData.from_acquisition_data(filtered_data)
        filtered_acquisition_data.set_objective_function(objective_function)
        objective_function.set_acquisition_data(filtered_acquisition_data)

        for _ in range(num_steps):
            model.update(objective_function.gradient(model))

        if locally_optimal:
            model.update(objective_function.locally_optimal_step(model))

        if verbose:
            print(f"Steepest ascent completed. Objective function value: {objective_function.value(model)}")

        if plot:
            # Add plotting code here

        return model
    except Exception as e:
        print(f"Error: {e}")
        sys.exit(1)

if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument("engine", help="Reconstruction engine module")
    parser.add_argument("data_file", help="Path to the raw data file")
    parser.add_argument("--steps", type=int, default=100, help="Number of steepest descent steps")
    parser.add_argument("--locally_optimal", action="store_true", help="Use locally optimal steepest ascent")
    parser.add_argument("--verbose", action="store_true", help="Print verbose output")
    parser.add_argument("--plot", action="store_true", help="Show plots")

    args = parser.parse_args()

    engine_module = __import__(args.engine, fromlist=["MyReconstructionEngine"])
    engine = engine_module.MyReconstructionEngine

    data = NiftiImageData.read_from_file(args.data_file)

    model = perform_steepest_ascent(data, engine, TestSTIRObjectiveFunction, args.steps, args.locally_optimal, args.verbose, args.plot)