test_pipeline.py 文件源码

def test_pipeline_init():
    # Test the various init parameters of the pipeline.
    assert_raises(TypeError, Pipeline)
    # Check that we can't instantiate pipelines with objects without fit
    # method
    pipe = assert_raises(TypeError, Pipeline, [('svc', IncorrectT)])
    # Smoke test with only an estimator
    clf = T()
    pipe = Pipeline([('svc', clf)])
    assert_equal(pipe.get_params(deep=True),
                 dict(svc__a=None, svc__b=None, svc=clf,
                      **pipe.get_params(deep=False)))

    # Check that params are set
    pipe.set_params(svc__a=0.1)
    assert_equal(clf.a, 0.1)
    assert_equal(clf.b, None)
    # Smoke test the repr:
    repr(pipe)

    # Test with two objects
    clf = SVC()
    filter1 = SelectKBest(f_classif)
    pipe = Pipeline([('anova', filter1), ('svc', clf)])

    # Check that we can't use the same stage name twice
    assert_raises(ValueError, Pipeline, [('svc', SVC()), ('svc', SVC())])

    # Check that params are set
    pipe.set_params(svc__C=0.1)
    assert_equal(clf.C, 0.1)
    # Smoke test the repr:
    repr(pipe)

    # Check that params are not set when naming them wrong
    assert_raises(ValueError, pipe.set_params, anova__C=0.1)

    # Test clone
    pipe2 = clone(pipe)
    assert_false(pipe.named_steps['svc'] is pipe2.named_steps['svc'])

    # Check that apart from estimators, the parameters are the same
    params = pipe.get_params(deep=True)
    params2 = pipe2.get_params(deep=True)

    for x in pipe.get_params(deep=False):
        params.pop(x)

    for x in pipe2.get_params(deep=False):
        params2.pop(x)

    # Remove estimators that where copied
    params.pop('svc')
    params.pop('anova')
    params2.pop('svc')
    params2.pop('anova')
    assert_equal(params, params2)