| Code derived from the d3.js 'force' example: | |
| The miserables.json file contains the weighted network of coappearances of | |
| characters in Victor Hugo's novel /Les Miserables/. Nodes represent characters | |
| as indicated by the labels, and edges connect any pair of characters that | |
| appear in the same chapter of the book. The values on the edges are the number | |
| of such coappearances. The data on coappearances were taken from D. E. Knuth, | |
| "The Stanford GraphBase: A Platform for Combinatorial Computing", | |
| Addison-Wesley, Reading, MA (1993). |
| (function(global, _) { | |
| var Miso = (global.Miso || (global.Miso = {})); | |
| /** | |
| * Smart delimited data parser. | |
| * - Handles CSV and other delimited data. | |
| * - Includes auto-guessing of delimiter character if delimiter is set to "auto" | |
| * Parameters: | |
| * options |
| <!DOCTYPE html> | |
| <meta charset="utf-8"> | |
| <style> | |
| .graticule { | |
| fill: none; | |
| stroke: #777; | |
| } | |
| .boundary { |
This hexbin map shows the proximity of earthquakes (magnitude 3.0 or greater) in the Canterbury region of New Zealand during the month of September, 2010.
The map is created using Leaflet. The hexbin layer is a custom Leaflet layer which uses d3js to generate a svg hexbin overlay. The source for the custom leaflet layer is viewable here.
Earthquake data sourced from GeoNet.
| <!DOCTYPE html> | |
| <meta charset="utf-8"> | |
| <style> | |
| .graticule { | |
| fill: none; | |
| stroke: #777; | |
| } | |
| .boundary { |
Sample output from Andrew Brown’s excellent Minecraft Overviewer.
This is a D3.js Heatmap example showing how the highest sun position of the day (which directly correlates with average temperature) changes over the year depending on the latitude of the place. The actual temperature chart would be shifted to the right a bit beacuse of thermal lag.
The data for the chart is calculated using SunCalc.
| // polyfill window.getMatchedCSSRules() in FireFox 6+ | |
| if ( typeof window.getMatchedCSSRules !== 'function' ) { | |
| var ELEMENT_RE = /[\w-]+/g, | |
| ID_RE = /#[\w-]+/g, | |
| CLASS_RE = /\.[\w-]+/g, | |
| ATTR_RE = /\[[^\]]+\]/g, | |
| // :not() pseudo-class does not add to specificity, but its content does as if it was outside it | |
| PSEUDO_CLASSES_RE = /\:(?!not)[\w-]+(\(.*\))?/g, | |
| PSEUDO_ELEMENTS_RE = /\:\:?(after|before|first-letter|first-line|selection)/g; | |
| // convert an array-like object to array |
| # For each day, find the appropriate Poisson Parameter and use it to calculate the likelihood of the actual view count | |
| # Likelihood = P(D|H) | |
| Calc.Likelihood <- function(changes, poissons, stats, periods) { | |
| likelihood <- 0 | |
| for (day in 1:nrow(stats)) { | |
| proceed <- FALSE | |
| period <- 1 | |
| while (!proceed) { | |
| if (day < changes[period]) { |