Fixes circular imports

[ngupta23]

Related Issuse or bug

There were circular imports when ModelContainer and MetricsContainer were imported in the same file. Fixed this.
Also, cleaned up some unit tests for time_series

Type of change

Please delete options that are not relevant.

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Code style update (formatting, local variables)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

How Has This Been Tested?

Unit Tests are passing.

Checklist:

• My code follows the style guidelines of this project.
• I have performed a self-review of my own code.
• I have commented my code, particularly in hard-to-understand areas.
• I have made corresponding changes to the documentation.
• My changes generate no new warnings.
• I have added tests that prove my fix is effective or that my feature works.
• New and existing unit tests pass locally with my changes.
• Any dependent changes have been merged and published in downstream modules.

[TremaMiguel]

I think that here when pytest collects the test it would not report the tests as separate

test_time_series.py::test_create_model[8-ARIMA]                   
test_time_series.py::test_create_model[6-Polynomial]
test_time_series.py::test_create_model[7-ETS]

maybe there's a way to yield the results from fixtures or passing the results from the fixture throught the argvalues argument of pytest.mark.parametrize.

Some references: here, here and here

[ngupta23]

Thanks @TremaMiguel , Yes, it would be nice to convert it to a parameterized test. I will experiment more with it before the next PR. Thanks for the references.

[TremaMiguel]

Looks like one can pass a function to pytest.mark.parametrize() , for example,

def model_parameters():

    globals_dict = {"seed": 0, "n_jobs_param": -1}
    model_containers = get_all_model_containers(globals_dict)

    model_names_ = []
    for model_name in model_containers.keys():
        if not model_name.startswith(("ensemble")):
            model_names_.append(model_name)

    parameters = [
        (name, np.arange(1, randint(6, 24)) if i%2==0  else randint(6, 24))
        for i, name in enumerate(model_names_)
    ]

    return parameters

this function can be called inside test_create_model

@pytest.mark.parametrize("model_parameter", model_parameters())
def test_create_model(load_setup, model_parameter, load_data):
    """test create_model functionality
    """
    exp = TimeSeriesExperiment()
    name, fh = model_parameter
    # Need to create individual setup for each model since the `fh` will be different for all models
    exp.setup(
        data=load_data, fold=3, fh=fh, fold_strategy="expandingwindow", verbose=False
    )
    model_obj = exp.create_model(name)

    y_pred = model_obj.predict()
    assert isinstance(y_pred, pd.Series)

    fh_index = fh if isinstance(fh, int) else fh[-1]
    expected_period_index = load_data.iloc[-fh_index:].index
    assert np.all(y_pred.index == expected_period_index)

will be adding this in my next PR.

[ngupta23]

I will merge this since @Yard1 already reviewed it in person.