I wrote another genetic algorithm library for go

<p>Hey everyone,</p> <p>Looking for some feedback on a genetic algorithm library I&#39;ve been working on for a little while now: <a href="https://github.com/tomcraven/goga">https://github.com/tomcraven/goga</a></p> <p>I&#39;ve written a couple of test apps to show it off. The most visual being an image matcher. It takes an input image and tries to get as close to it as it can only using RGBA coloured rects and circles. Here&#39;s the end result of it trying to match mona lisa (input, output and overlaid):</p> <p><a href="http://imgur.com/a/Sr7iD">http://imgur.com/a/Sr7iD</a></p> <p>Thanks for reading and any feedback.</p> <hr/>**评论：**<br/><br/>sharptierce: <pre><p>interesting library! </p> <p>About feedback: you should read (<a href="https://golang.org/doc/effective_go.html#names" rel="nofollow">https://golang.org/doc/effective_go.html#names</a>), because all those IFoobar interfaces are not really best practice. </p></pre>