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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def ihfft(a, n=None, axis=-1, norm=None):
 """ Compute the inverse FFT of a signal which has Hermitian symmetry. Parameters a : array_like Input array. n : int, optional Length of the inverse FFT. Number of points along transformation axis in the input to use. If `n` is smaller than the length of the input, the input is cropped. If it is larger, the input is padded with zeros. If `n` is not given, the length of the input along the axis specified by `axis` is used. axis : int, optional Axis over which to compute the inverse FFT. If not given, the last axis is used. norm : {None, "ortho"}, optional .. versionadded:: 1.10.0 Normalization mode (see `numpy.fft`). Default is None. Returns ------- out : complex ndarray The truncated or zero-padded input, transformed along the axis indicated by `axis`, or the last one if `axis` is not specified. If `n` is even, the length of the transformed axis is ``(n/2)+1``. If `n` is odd, the length is ``(n+1)/2``. See also -------- hfft, irfft Notes ----- `hfft`/`ihfft` are a pair analogous to `rfft`/`irfft`, but for the opposite case: here the signal has Hermitian symmetry in the time domain and is real in the frequency domain. So here it's `hfft` for which you must supply the length of the result if it is to be odd: ``ihfft(hfft(a), len(a)) == a``, within numerical accuracy. Examples -------- array([ 1.+0.j, 2.-0.j, 3.+0.j, 4.+0.j, 3.+0.j, 2.-0.j]) array([ 1.-0.j, 2.-0.j, 3.-0.j, 4.-0.j]) """

    # The copy may be required for multithreading.
    a = array(a, copy=True, dtype=float)
    if n is None:
        n = a.shape[axis]
    unitary = _unitary(norm)
    output = conjugate(rfft(a, n, axis))
    return output * (1 / (sqrt(n) if unitary else n))