73 lines
1.8 KiB
Python
73 lines
1.8 KiB
Python
import multiprocessing
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from pathlib import Path
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import matplotlib.pyplot as plt
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import numpy as np
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import scgenerator as sc
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PARAMS = Path("./examples/noisy.toml")
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SEED = 2564
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def path(i) -> Path:
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return Path(f"build/{Path(__file__).stem}_{i}.zip")
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def propagate(i):
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np.random.seed(SEED + i)
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params = sc.Parameters.load("./examples/noisy.toml")
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sc.propagation(path(i), params.compile()).simulate()
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def propagate_all(n):
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to_do = [i for i in range(n) if not path(i).exists()]
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with multiprocessing.Pool(4) as pool:
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pool.map(propagate, to_do)
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spec, props = sc.propagation_series([path(i) for i in range(n)])
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return spec, props
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def quick_test():
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t = sc.tspace(dt=1e-15, t_num=2048)
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spec_0 = np.fft.fft(10e3 * np.exp(-((t / 70e-15) ** 2)))
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spec = sc.Spectrum(
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[np.exp(2j * np.pi * np.random.rand()) + spec_0 for _ in range(20)],
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sc.wspace(t) + sc.units.nm_rads(800),
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t,
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)
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_, (top, bot) = plt.subplots(2, 1, constrained_layout=True, height_ratios=[1, 5], sharex=True)
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bot.plot(spec.wl_disp * 1e9, spec[0].wl_int)
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top.plot(spec.wl_disp * 1e9, spec.coherence())
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top.set_xlim(750, 850)
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bot.set_yscale("log")
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plt.show()
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def main():
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n = 1
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spec, props = propagate_all(n)
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print(spec.shape)
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wl, ind, _ = sc.PlotRange(
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spec.wl_disp[spec.wl_disp > 0].min() * 1e9,
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props.parameters.wavelength_window[1] * 1e9,
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"nm",
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).sort_axis(spec.wl_disp)
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for i in range(spec.shape[1]):
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fig, (left, right) = plt.subplots(1, 2)
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for s in spec[:, i].time_int:
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left.plot(spec.t, s)
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for s in spec[:, i].wl_int:
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right.plot(wl, s[ind])
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plt.show()
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if __name__ == "__main__":
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quick_test()
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# main()
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