# Buggy code
def irfft(a, n=None, axis=-1, norm=None):
    """
    Compute the inverse of the n-point DFT for real input.

    This function computes the inverse of the one-dimensional *n*-point
    discrete Fourier Transform of real input computed by `rfft`.
    In other words, ``irfft(rfft(a), len(a)) == a`` to within numerical
    accuracy. (See Notes below for why ``len(a)`` is necessary here.)

    The input is expected to be in the form returned by `rfft`, i.e. the
    real zero-frequency term followed by the complex positive frequency terms
    in order of increasing frequency.  Since the discrete Fourier Transform of
    real input is Hermitian-symmetric, the negative frequency terms are taken
    to be the complex conjugates of the corresponding positive frequency terms.

    Parameters
    ----------
    a : array_like
        The input array.
    n : int, optional
        Length of the transformed axis of the output.
        For `n` output points, ``n//2+1`` input points are necessary.  If the
        input is longer than this, it is cropped.  If it is shorter than this,
        it is padded with zeros.  If `n` is not given, it is taken to be
        ``2*(m-1)`` where ``m`` is the length of the input along the axis
        specified by `axis`.
    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 : ndarray
        The truncated or zero-padded input, transformed along the axis
        indicated by `axis`, or the last one if `axis` is not specified.
        The length of the transformed axis is `n`, or, if `n` is not given,
        ``2*(m-1)`` where ``m`` is the length of the transformed axis of the
        input. To get an odd number of output points, `n` must be specified.

    Raises
    ------
    IndexError
        If `axis` is larger than the last axis of `a`.

    See Also
    --------
    numpy.fft : For definition of the DFT and conventions used.
    rfft : The one-dimensional FFT of real input, of which `irfft` is inverse.
    fft : The one-dimensional FFT.
    irfft2 : The inverse of the two-dimensional FFT of real input.
    irfftn : The inverse of the *n*-dimensional FFT of real input.

    Notes
    -----
    Returns the real valued `n`-point inverse discrete Fourier transform
    of `a`, where `a` contains the non-negative frequency terms of a
    Hermitian-symmetric sequence. `n` is the length of the result, not the
    input.

    If you specify an `n` such that `a` must be zero-padded or truncated, the
    extra/removed values will be added/removed at high frequencies. One can
    thus resample a series to `m` points via Fourier interpolation by:
    ``a_resamp = irfft(rfft(a), m)``.

    The correct interpretation of the hermitian input depends on the length of
    the original data, as given by `n`. This is because each input shape could
    correspond to either an odd or even length signal. By default, `irfft`
    assumes an even output length which puts the last entry at the Nyquist
    frequency; aliasing with its symmetric counterpart. By Hermitian symmetry,
    the value is thus treated as purely real. To avoid losing information, the
    correct length of the real input **must** be given.

    Examples
    --------
    >>> np.fft.ifft([1, -1j, -1, 1j])
    array([0.+0.j,  1.+0.j,  0.+0.j,  0.+0.j]) # may vary
    >>> np.fft.irfft([1, -1j, -1])
    array([0.,  1.,  0.,  0.])

    Notice how the last term in the input to the ordinary `ifft` is the
    complex conjugate of the second term, and the output has zero imaginary
    part everywhere.  When calling `irfft`, the negative frequencies are not
    specified, and the output array is purely real.

    """
    a = asarray(a)
    if n is None:
        n = (a.shape[axis] - 1) * 2
    fct = 1 / n
    if norm is not None and _unitary(norm):
        fct = 1 / sqrt(n)
    output = _raw_fft(a, n, axis, True, False, fct)
    return output


# Traceback (ZeroDivisionError)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<__array_function__ internals>", line 6, in ifft
File "/home/peter/.local/lib/python3.7/site-packages/numpy/fft/pocketfft.py", line 274, in ifft
fct = 1/n
ZeroDivisionError: division by zero

# Fixed code
def irfft(a, n=None, axis=-1, norm=None):
    """
    Compute the inverse of the n-point DFT for real input.

    This function computes the inverse of the one-dimensional *n*-point
    discrete Fourier Transform of real input computed by `rfft`.
    In other words, ``irfft(rfft(a), len(a)) == a`` to within numerical
    accuracy. (See Notes below for why ``len(a)`` is necessary here.)

    The input is expected to be in the form returned by `rfft`, i.e. the
    real zero-frequency term followed by the complex positive frequency terms
    in order of increasing frequency.  Since the discrete Fourier Transform of
    real input is Hermitian-symmetric, the negative frequency terms are taken
    to be the complex conjugates of the corresponding positive frequency terms.

    Parameters
    ----------
    a : array_like
        The input array.
    n : int, optional
        Length of the transformed axis of the output.
        For `n` output points, ``n//2+1`` input points are necessary.  If the
        input is longer than this, it is cropped.  If it is shorter than this,
        it is padded with zeros.  If `n` is not given, it is taken to be
        ``2*(m-1)`` where ``m`` is the length of the input along the axis
        specified by `axis`.
    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 : ndarray
        The truncated or zero-padded input, transformed along the axis
        indicated by `axis`, or the last one if `axis` is not specified.
        The length of the transformed axis is `n`, or, if `n` is not given,
        ``2*(m-1)`` where ``m`` is the length of the transformed axis of the
        input. To get an odd number of output points, `n` must be specified.

    Raises
    ------
    IndexError
        If `axis` is larger than the last axis of `a`.

    See Also
    --------
    numpy.fft : For definition of the DFT and conventions used.
    rfft : The one-dimensional FFT of real input, of which `irfft` is inverse.
    fft : The one-dimensional FFT.
    irfft2 : The inverse of the two-dimensional FFT of real input.
    irfftn : The inverse of the *n*-dimensional FFT of real input.

    Notes
    -----
    Returns the real valued `n`-point inverse discrete Fourier transform
    of `a`, where `a` contains the non-negative frequency terms of a
    Hermitian-symmetric sequence. `n` is the length of the result, not the
    input.

    If you specify an `n` such that `a` must be zero-padded or truncated, the
    extra/removed values will be added/removed at high frequencies. One can
    thus resample a series to `m` points via Fourier interpolation by:
    ``a_resamp = irfft(rfft(a), m)``.

    The correct interpretation of the hermitian input depends on the length of
    the original data, as given by `n`. This is because each input shape could
    correspond to either an odd or even length signal. By default, `irfft`
    assumes an even output length which puts the last entry at the Nyquist
    frequency; aliasing with its symmetric counterpart. By Hermitian symmetry,
    the value is thus treated as purely real. To avoid losing information, the
    correct length of the real input **must** be given.

    Examples
    --------
    >>> np.fft.ifft([1, -1j, -1, 1j])
    array([0.+0.j,  1.+0.j,  0.+0.j,  0.+0.j]) # may vary
    >>> np.fft.irfft([1, -1j, -1])
    array([0.,  1.,  0.,  0.])

    Notice how the last term in the input to the ordinary `ifft` is the
    complex conjugate of the second term, and the output has zero imaginary
    part everywhere.  When calling `irfft`, the negative frequencies are not
    specified, and the output array is purely real.

    """
    a = asarray(a)
    if n is None:
        n = (a.shape[axis] - 1) * 2
    inv_norm = n
    if norm is not None and _unitary(norm):
        inv_norm = sqrt(n)
    output = _raw_fft(a, n, axis, True, False, inv_norm)
    return output