46 lines
1.3 KiB
Python
46 lines
1.3 KiB
Python
import numpy as np
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from scipy import fft
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from scipy import signal as sgl
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from scipy import optimize as opti
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def reflex3s(eta, x, h, f):
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eta_psd = np.stack([fft.rfft(z) for z in eta])
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f_psd = fft.rfftfreq(eta.shape[1], 1 / f)
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eta_amp = np.abs(eta_psd) / (f_psd.size - 1)
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eta_phase = np.angle(eta_psd)
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g = 9.81
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k = np.asarray(
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[
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opti.root_scalar(
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f=lambda k: k * np.tanh(k) - (2 * np.pi * f) ** 2 / g * h,
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fprime=lambda k: np.tanh(k) + k * (1 - np.tanh(k) ** 2),
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x0=0.5,
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).root
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/ h
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for f in f_psd
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]
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)
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s1 = 1 + np.exp(2j * k * (x[1] - x[0])) + np.exp(2j * k * (x[2] - x[0]))
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s2 = 1 + np.exp(-2j * k * (x[1] - x[0])) + np.exp(-2j * k * (x[2] - x[0]))
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s12 = 3
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s3 = (
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eta_amp[0] * np.exp(-1j * (eta_phase[0]))
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+ eta_amp[1] * np.exp(-1j * (eta_phase[1] - k * (x[1] - x[0])))
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+ eta_amp[2] * np.exp(-1j * (eta_phase[2] - k * (x[2] - x[0])))
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)
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s4 = (
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eta_amp[0] * np.exp(-1j * (eta_phase[0]))
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+ eta_amp[1] * np.exp(-1j * (eta_phase[1] + k * (x[1] - x[0])))
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+ eta_amp[2] * np.exp(-1j * (eta_phase[2] + k * (x[2] - x[0])))
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)
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s5 = s1 * s2 - s12**2
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ai = np.abs((s2 * s3 - s12 * s4) / s5)
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ar = np.abs((s1 * s4 - s12 * s3) / s5)
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return f_psd, ai, ar
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