Oh I see. Yeah that would be better. I'll do that tomorrow. I think the<br>
style issues are solved at my latest commit, please tell me if there's<br>
anything that I forgot :)<br>
<br>
On Tue, Apr 5, 2016 at 10:33 PM, Ryan Curtin <notifications@github.com><br>
wrote:<br>
<br>
> Ah, yeah, what I mean is that we should split each of the five things you<br>
> are testing into separate test cases. Like this:<br>
><br>
> //Test: Run LSH with varying number of tables, keeping all other parameters<br>
> //constant. Compute the recall, i.e. the number of reported neighbors that<br>
> //are real neighbors of the query.<br>
> //LSH's property is that (with high probability), increasing the number of<br>
> //tables will increase recall. Epsilon ensures that if noise lightly affects<br>
> //the projections, the test will not fail.<br>
> //This produces false negatives, so we attempt the test numTries times and<br>
> //only declare failure if all of them fail.<br>
> BOOST_AUTO_TEST_CASE(RecallTest)<br>
> {<br>
> // code here<br>
> }<br>
><br>
> //Test: Run LSH with varying hash width, keeping all other parameters<br>
> //constant. Compute the recall, i.e. the number of reported neighbors that<br>
> //are real neighbors of the query.<br>
> //LSH's property is that (with high probability), increasing the hash width<br>
> //will increase recall. Epsilon ensures that if noise lightly affects the<br>
> //projections, the test will not fail.<br>
> BOOST_AUTO_TEST_CASE(HashWidthTest)<br>
> {<br>
> // code here<br>
> }<br>
><br>
> I hope I've described that well enough, let me know if not. The basic idea<br>
> is that we can split each of the tests so that a user can run only one test<br>
> at a time. The disadvantage to this approach is that you probably have to<br>
> load a dataset multiple times, but that's not so huge of a deal since the<br>
> dataset will be relatively small.<br>
><br>
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