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Spectral denoising: for single spectrum
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The ``spectral_denoising`` function, which is the core function of the project, removes noise ions in MS/MS spectra. 

The function essentially is a warpper function for performing ``electronic_denoising`` and ``formula_denoising`` functions in sequence. Just like ``formula_denoising``, ``spectral_denoising`` also requires molecular information (SMILES/formula and adduct) to remove noise ions. For details about this please find in the 'fomulra denoising' section.
If no valid ion was left after electronic denoising, the function will return nan.

Example usage:

.. code-block:: python

    import spectral_denoising as sd
    from spectral_denoising.noise import *
    from spectral_denoising.spectral_operations import *
    from spectral_denoising.chem_utils import *
    peak = np.array([[48.992496490478516 ,154.0],
                  [63.006099700927734, 265.0],
                  [79.02062225341797, 521.0]], dtype = np.float32)
    noise = generate_noise(pmz, lamda=10, n = 50)
    smiles = 'O=c1nc[nH]c2nc[nH]c12'
    adduct = '[M+Na]+'
    pmz = calculate_precursormz(adduct,smiles)
    peak_with_noise = add_noise(peak, noise)
    peak_denoised = sd.spectral_denoising(peak_with_noise, smiles, adduct)
    print(f'Entropy similarity of spectra with noise: {sd.entropy_similairty(peak_with_noise,peak, pmz ):.2f}.')
    print(f'Entropy similarity of spectra with noise: {sd.entropy_similairty(peak_denoised,peak, pmz ):.2f}.')

The output will be:

.. code-block:: python

    Entropy similarity of spectra with noise: 0.47.
    Entropy similarity of spectra with noise: 0.99.

References
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.. autofunction:: spectral_denoising.spectral_denoising
    :noindex: