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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 unique_float(data, return_index=False, return_inverse=False, digits=None):
 """ Identical to the numpy.unique command, except evaluates floating point numbers, using a specified number of digits. If digits isn't specified, the library default TOL_MERGE will be used. """

    data = np.asanyarray(data)
    as_int = float_to_int(data, digits)
    _junk, unique, inverse = np.unique(as_int,
                                       return_index=True,
                                       return_inverse=True)

    if (not return_index) and (not return_inverse):
        return data[unique]

    result = [data[unique]]

    if return_index:
        result.append(unique)
    if return_inverse:
        result.append(inverse)
    return tuple(result)