attoworld

import numpy as np import os from attoworld.frog.interface import FROG from attoworld.frog.frog_config import FROG_CONFIG # 1. Create a dummy FROG trace file for demonstration dummy_file_path = "dummy_frog_trace.dat" delay_axis = np.linspace(-100, 100, 128) # fs freq_axis = np.linspace(2.0, 4.0, 128) # PHz dummy_trace = np.random.rand(128, 128) * 100 + 10 # Base noise dummy_trace[40:80, 40:80] += 500 # Add a feature to the trace with open(dummy_file_path, "w") as f: f.write("# FROG trace data\n") f.write(f"# delay_axis {delay_axis.min()} {delay_axis.max()} {len(delay_axis)}\n") f.write(f"# freq_axis {freq_axis.min()} {freq_axis.max()} {len(freq_axis)}\n") np.savetxt(f, dummy_trace) # 2. Initialize FROG processor and load the trace frog_processor = FROG() frog_processor.load_trace(dummy_file_path) # 3. Configure FROG reconstruction settings config = FROG_CONFIG() config.max_iter = 10 # Keep iterations low for quick execution config.pulse_width_estimate_fs = 50 config.wavelength_center_nm = 800 config.delay_steps = len(delay_axis) config.freq_steps = len(freq_axis) config.delay_max = delay_axis.max() config.delay_min = delay_axis.min() config.freq_max = freq_axis.max() config.freq_min = freq_axis.min() # 4. Perform reconstruction print("Starting FROG reconstruction...") frog_processor.reconstruct(config) print("Reconstruction complete.") # 5. Access results reconstructed_pulse_intensity = frog_processor.reconstructed_intensity print(f"Reconstructed pulse intensity shape: {reconstructed_pulse_intensity.shape}") # 6. Clean up the dummy file os.remove(dummy_file_path)