问Python中与类相关的代码片段的解释

EN

from sklearn.base import BaseEstimator, TransformerMixin
    
    # column index
    rooms_ix, bedrooms_ix, population_ix, households_ix = 3, 4, 5, 6
    
    class CombinedAttributesAdder(BaseEstimator, TransformerMixin):
        def __init__(self, add_bedrooms_per_room=True): # no *args or **kargs
            self.add_bedrooms_per_room = add_bedrooms_per_room
        def fit(self, X, y=None):
            return self  # nothing else to do
        def transform(self, X):
            rooms_per_household = X[:, rooms_ix] / X[:, households_ix]
            population_per_household = X[:, population_ix] / X[:, households_ix]
            if self.add_bedrooms_per_room:
                bedrooms_per_room = X[:, bedrooms_ix] / X[:, rooms_ix]
                return np.c_[X, rooms_per_household, population_per_household,
                             bedrooms_per_room]
            else:
                return np.c_[X, rooms_per_household, population_per_household]
    
    attr_adder = CombinedAttributesAdder(add_bedrooms_per_room=False)
    housing_extra_attribs = attr_adder.transform(housing.values)