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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 generic_distribution(target, seeds, func):
 r""" Accepts an 'rv_frozen' object from the Scipy.stats submodule and returns values from the distribution for the given seeds This uses the ``ppf`` method of the stats object Parameters target : OpenPNM Object The object which this model is associated with. This controls the length of the calculated array, and also provides access to other necessary properties. seeds : string, optional The dictionary key on the Geometry object containing random seed values (between 0 and 1) to use in the statistical distribution. func : object An 'rv_frozen' object from the Scipy.stats library with all of the parameters pre-specified. Examples -------- The following code illustrates the process of obtaining a 'frozen' Scipy stats object and adding it as a model: Now retrieve the stats distribution and add to ``geo`` as a model: """

    seeds = target[seeds]
    value = func.ppf(seeds)
    return value