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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 deframesig(frames, siglen, frame_len, frame_step, winfunc=lambda x: numpy.ones((x,))):
 """Does overlap-add procedure to undo the action of framesig. :param frames: the array of frames. :param siglen: the length of the desired signal, use 0 if unknown. Output will be truncated to siglen samples. :param frame_len: length of each frame measured in samples. :param frame_step: number of samples after the start of the previous frame that the next frame should begin. :param winfunc: the analysis window to apply to each frame. By default no window is applied. :returns: a 1-D signal. """

    frame_len = round_half_up(frame_len)
    frame_step = round_half_up(frame_step)
    numframes = numpy.shape(frames)[0]
    assert numpy.shape(frames)[1] == frame_len, '"frames" matrix is wrong size, 2nd dim is not equal to frame_len'

    indices = numpy.tile(numpy.arange(0, frame_len), (numframes, 1)) + numpy.tile(
        numpy.arange(0, numframes * frame_step, frame_step), (frame_len, 1)).T
    indices = numpy.array(indices, dtype=numpy.int32)
    padlen = (numframes - 1) * frame_step + frame_len

    if siglen <= 0: siglen = padlen

    rec_signal = numpy.zeros((padlen,))
    window_correction = numpy.zeros((padlen,))
    win = winfunc(frame_len)

    for i in range(0, numframes):
        window_correction[indices[i, :]] = window_correction[
                                               indices[i, :]] + win + 1e-15  # add a little bit so it is never zero
        rec_signal[indices[i, :]] = rec_signal[indices[i, :]] + frames[i, :]

    rec_signal = rec_signal / window_correction
    return rec_signal[0:siglen]