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#expressiverangeanalysis

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Mark Gritter<p>For $PROJECT I am wondering how sparse a bitmap needs to be before it's worth looking at alternatives.</p><p>Say I have a 32-bit random seed and it produces a tuple (x_1, x_2, ..., x_n) of attributes through some process we want to analyze. What I'd like is to build an index that lets me identify seed values with, say, x_1=4, or quickly intersect several indexes to find a seed value with x_1=4 and x_2 = 13 and x_3 = 5.</p><p>If the domain of x_i is small (say, 16 different values) then we could use a bunch of bitmaps -- they're only 512MiB each. Each bitmap will be only 6% populated, is that enough to consider a fancier representation that compresses the bitmap?</p><p>I've read "Searchable compressed representations of very sparse bitmaps" <a href="https://www.stevenpigeon.com/Publications/publications/SparseBitmap.pdf" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">stevenpigeon.com/Publications/</span><span class="invisible">publications/SparseBitmap.pdf</span></a> but my feeling right now is this isn't a good fit.</p><p>There are a bunch of ideas of the form "index a collection of containers, which may be arrays or compressed arrays or bitmaps" which probably only work well when the set is not very evenly distributed.</p><p><a href="https://mathstodon.xyz/tags/DataStructures" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataStructures</span></a> <a href="https://mathstodon.xyz/tags/ExpressiveRangeAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ExpressiveRangeAnalysis</span></a></p>
Mark Gritter<p>First sampling run of the <a href="https://mathstodon.xyz/tags/Rogue" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Rogue</span></a> (-ish) room generation algorithm. This ASCII diagram shows the proportion of samples that each square on the map is occupied by a room (including walls). For example, 6 = 60-70% of samples, 0 = less than 10%.</p><p>13.125 seconds for 1m samples gives an estimated time of 15.7 hours to sweep the whole 32-bit space of possible seeds. Totally doable, and not even parallelized yet.</p><p><a href="https://mathstodon.xyz/tags/ProceduralContentGeneration" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ProceduralContentGeneration</span></a> <a href="https://mathstodon.xyz/tags/ExpressiveRangeAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ExpressiveRangeAnalysis</span></a></p>
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