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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 convolve(data, kernel, method='scipy'):
 r"""Convolve data with kernel This method convolves the input data with a given kernel using FFT and is the default convolution used for all routines Parameters data : np.ndarray Input data array, normally a 2D image kernel : np.ndarray Input kernel array, normally a 2D kernel method : str {'astropy', 'scipy'}, optional Convolution method (default is 'scipy') Returns ------- np.ndarray convolved data Raises ------ ValueError If `data` and `kernel` do not have the same number of dimensions ValueError If `method` is not 'astropy' or 'scipy' Notes ----- The convolution methods are: 'astropy': Uses the astropy.convolution.convolve_fft method provided in Astropy (http://www.astropy.org/) 'scipy': Uses the scipy.signal.fftconvolve method provided in SciPy (https://www.scipy.org/) Examples -------- array([[ 534., 525., 534.], [ 453., 444., 453.], [ 534., 525., 534.]]) array([[ 86., 170., 146.], [ 246., 444., 354.], [ 290., 494., 374.]]) """


    if data.ndim != kernel.ndim:
        raise ValueError('Data and kernel must have the same dimensions.')

    if method not in ('astropy', 'scipy'):
        raise ValueError('Invalid method. Options are "astropy" or "scipy".')

    if not import_astropy:  # pragma: no cover
        method = 'scipy'

    if method == 'astropy':
        return convolve_fft(data, kernel, boundary='wrap', crop=False,
                            nan_treatment='fill', normalize_kernel=False)

    elif method == 'scipy':
        return scipy.signal.fftconvolve(data, kernel, mode='same')