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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 parallel_snr_func(num, binary_args, phenomdwave, signal_type, noise_interpolants, prefactor, verbose):
 """SNR calulation with PhenomDWaveforms Generate PhenomDWaveforms and calculate their SNR against sensitivity curves. Args: num (int):
 Process number. If only a single process, num=0. binary_args (tuple):
 Binary arguments for :meth:`gwsnrcalc.utils.waveforms.EccentricBinaries.__call__`. phenomdwave (obj):
 Initialized class of :class:`gwsnrcalc.utils.waveforms.PhenomDWaveforms`. signal_type (list of str):
 List with types of SNR to calculate. Options are `all` for full wavefrom, `ins` for inspiral, `mrg` for merger, and/or `rd` for ringdown. noise_interpolants (dict):
 All the noise noise interpolants generated by :mod:`gwsnrcalc.utils.sensitivity`. prefactor (float):
 Prefactor to multiply SNR by (not SNR^2). verbose (int):
 Notify each time ``verbose`` processes finish. If -1, then no notification. Returns: (dict):
 Dictionary with the SNR output from the calculation. """


    wave = phenomdwave(*binary_args)

    out_vals = {}

    for key in noise_interpolants:
        hn_vals = noise_interpolants[key](wave.freqs)
        snr_out = csnr(wave.freqs, wave.hc, hn_vals,
                       wave.fmrg, wave.fpeak, prefactor=prefactor)

        if len(signal_type) == 1:
            out_vals[key + '_' + signal_type[0]] = snr_out[signal_type[0]]
        else:
            for phase in signal_type:
                out_vals[key + '_' + phase] = snr_out[phase]
    if verbose > 0 and (num+1) % verbose == 0:
        print('Process ', (num+1), 'is finished.')

    return out_vals