{"url":"https://api.github.com/gists/582915","forks_url":"https://api.github.com/gists/582915/forks","commits_url":"https://api.github.com/gists/582915/commits","id":"582915","node_id":"MDQ6R2lzdDU4MjkxNQ==","git_pull_url":"https://gist.github.com/582915.git","git_push_url":"https://gist.github.com/582915.git","html_url":"https://gist.github.com/582915","files":{".block":{"filename":".block","type":"text/plain","language":null,"raw_url":"https://gist.githubusercontent.com/mbostock/582915/raw/703d310b399098a243a76a50bc209167e924cfd2/.block","size":17,"truncated":false,"content":"license: gpl-3.0\n"},"README.md":{"filename":"README.md","type":"text/plain","language":"Markdown","raw_url":"https://gist.githubusercontent.com/mbostock/582915/raw/bbce0fb521ec64e2cd9c22c9a776184f29bbe630/README.md","size":742,"truncated":false,"content":"Streamgraphs are a generalization of [stacked area graphs](http://protovis.org/ex/stack.html) where the baseline is free. By shifting the baseline, it is possible to minimize the change in slope (or “wiggle”) in individual series, thereby making it easier to perceive the thickness of any given layer across the data. Byron & Wattenberg describe several streamgraph algorithms in [“Stacked Graphs—Geometry & Aesthetics”](http://www.leebyron.com/else/streamgraph/), several of which are implemented by `pv.Layout.Stack`. As additional examples, see stacked graphs of [employment](http://protovis.org/ex/jobs.html) and [unemployment](http://hci.stanford.edu/jheer/files/zoo/ex/time/stack.html) statistics.\n"},"index.html":{"filename":"index.html","type":"text/html","language":"HTML","raw_url":"https://gist.githubusercontent.com/mbostock/582915/raw/99222e123ab86c5c77fddba857272d10aa55166f/index.html","size":968,"truncated":false,"content":"\n \n Streamgraph\n \n \n \n \n \n \n \n"},"stream.js":{"filename":"stream.js","type":"application/javascript","language":"JavaScript","raw_url":"https://gist.githubusercontent.com/mbostock/582915/raw/5baff3a3282f08b7807261790eed23241da2decb/stream.js","size":754,"truncated":false,"content":"/* Inspired by Lee Byron's test data generator. */\nfunction layers(n, m) {\n function bump(a) {\n var x = 1 / (.1 + Math.random()),\n y = 2 * Math.random() - .5,\n z = 10 / (.1 + Math.random());\n for (var i = 0; i < m; i++) {\n var w = (i / m - y) * z;\n a[i] += x * Math.exp(-w * w);\n }\n }\n return pv.range(n).map(function() {\n var a = [], i;\n for (i = 0; i < m; i++) a[i] = 0;\n for (i = 0; i < 5; i++) bump(a);\n return a;\n });\n}\n\n/* Another layer generator using gamma distributions. */\nfunction waves(n, m) {\n return pv.range(n).map(function(i) {\n return pv.range(m).map(function(j) {\n var x = 20 * j / m - i / 3;\n return x > 0 ? 2 * x * Math.exp(-.5 * x) : 0;\n });\n });\n}"},"thumbnail.png":{"filename":"thumbnail.png","type":"image/png","language":null,"raw_url":"https://gist.githubusercontent.com/mbostock/582915/raw/3fb6b87364651456c68b4d8b8b0fc2e8ae65bf66/thumbnail.png","size":13144,"truncated":false,"content":"�PNG\r\n\u001A\n\u0000\u0000\u0000\rIHDR\u0000\u0000\u0000�\u0000\u0000\u0000x\b\u0006\u0000\u0000\u0000�\u0006��\u0000\u0000\u0000\u0019tEXtSoftware\u0000Adobe 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