# method_to_transform¶

gtda.mapper.utils.decorators.method_to_transform(cls, method_name)[source]

Wrap a class to add a transform method as an alias to an existing method.

An example of use is for classes possessing a score method such as kernel density estimators and anomaly/novelty detection estimators, to allow for these estimators are to be used as steps in a pipeline.

Parameters
• cls (object) – Class to be wrapped. If method_name is not one of its methods, transform always returns None.

• method_name (str) – Name of the method in cls to which transform will be an alias. The fist argument of this method becomes the X input for transform.

Returns

wrapped_cls – New class inheriting from sklearn.base.TransformerMixin, so that a fit_transform is also available. Its name is the name of cls prepended with 'Extended'.

Return type

object

Examples

>>> import numpy as np
>>> from numpy.testing import assert_almost_equal
>>> from sklearn.neighbors import KernelDensity
>>> from gtda.mapper import method_to_transform
>>> X = np.random.random((100, 2))
>>> kde = KernelDensity()
>>> kde_extended = method_to_transform(
...     KernelDensity, 'score_samples')()
>>> Xt = kde.fit(X).score_samples(X)
>>> Xt_extended = kde_extended.fit_transform(X)
>>> assert_almost_equal(Xt, Xt_extended)
True