Improve tests of filters

[caddycarine]

In the test_boolean_filtering() method, the filterset built for testing has all its classifier values set to true

classifiers = [
            "stochastic",
            "long_run_time",
            "manipulates_state",
            "manipulates_source",
            "inspects_source",
        ]

        comprehension, filterset = strategies, {}
        for classifier in classifiers:
            comprehension = set(
                filter(axl.Classifiers[classifier], strategies)
            ) & set(comprehension)
            filterset[classifier] = True
        filtered = set(
            axl.filtered_strategies(filterset, strategies=strategies)
        )
        self.assertEqual(comprehension, filtered)

Currently, there is no strategy that meets this criteria so the result is always an empty set, making the test a comparison of two empty sets.
Was thinking of creating a hypothesis decorator to return a list of classifiers to be given to this test so that it would not always be empty. The decorator could look like this:

classifier_list = draw(
        lists(sampled_from(classifiers), min_size=min_size, max_size=max_size, unique=True)
   )

[drvinceknight]

Using hypothesis to explore the space of all possible classifiers sounds good to me 👍

One immediate question that comes to mind is whether or not we need a new hypothesis decorator for this as I don't see much potential for reuse but that might not be a good reason anyway and this can be discussed on the PR :)

Go for it 👍 💪

[caddycarine]

The suggested changes have been done in #1377. Can this be closed?

[marcharper]

Yep! Next time you can say "closes #1377" in the PR comment (the text on github when you open the PR) and it will close the issue on merge.