import torch

def hilbert(h):
    window = 2 * torch.heaviside(torch.linspace(-1, 1, steps=h.size(-1)), values=torch.ones(1)).to(h.device)
    window = torch.flip(window, dims=(-1,))
    windowed_fft = window * torch.fft.fft(h)
    return torch.fft.ifft(windowed_fft)

def minimum_phase_version(h):
    """
    h is the time-domain RIR.
    We ensure that the RIR has minimum-phase-lag, which helps with stability, as its inverse is then causal and stable.
    """
    T_orig = h.size(-1)
    h = torch.nn.functional.pad(h, (0, T_orig))
    H = torch.fft.fft(h)
    log_H_abs = torch.log(torch.abs(H) + 1e-8)
    minimum_phase = - torch.imag( hilbert(log_H_abs) )
    exp_minimum_phase = torch.exp(1j*minimum_phase)

    minimum_phase_h = torch.real(torch.fft.ifft( torch.abs(H).type(exp_minimum_phase.dtype) * exp_minimum_phase )) # |H(w)|*e^(jPhi(w))
    minimum_phase_h = minimum_phase_h[: -T_orig]
    return minimum_phase_h