Actually use seedrandom.
The tests are run in a sandboxed environment, and so didn’t have access to the same global Math whose random was being overridden.
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@ -26,6 +26,11 @@ module.exports = function() {
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return topic;
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};
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topic.sandbox = function(_) {
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sandbox = _;
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return topic;
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};
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topic.document = function(_) {
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var document = jsdom.jsdom("<html><head></head><body></body></html>");
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@ -18,7 +18,7 @@ var suite = vows.describe("d3.random");
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suite.addBatch({
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"random": {
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topic: load("math/random").expression("d3.random"),
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topic: load("math/random").sandbox({Math: Math}).expression("d3.random"),
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"(using seedrandom)": {
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topic: function(random) {
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_random = Math.random;
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@ -75,14 +75,14 @@ function KSTest(cdf, n) {
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// Derivation of this interval is difficult.
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// @see K-S test in Knuth's AoCP vol.2
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assert.inDelta(K_positive, 0.723255, 0.794145);
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}
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};
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}
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// Logistic approximation to normal CDF around N(mean, stddev).
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function normalCDF(mean, stddev) {
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return function(x) {
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return 1 / (1 + Math.exp(-0.07056 * Math.pow((x-mean)/stddev, 3) - 1.5976 * (x-mean)/stddev));
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}
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};
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}
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// See http://en.wikipedia.org/wiki/Log-normal_distribution#Similar_distributions
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@ -91,7 +91,7 @@ function logNormalCDF(mean, stddev) {
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var numerator = Math.exp(mean);
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return function(x) {
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return 1 / (Math.pow(numerator / x, exponent) + 1);
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}
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};
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}
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function irwinHallCDF(n) {
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@ -111,7 +111,7 @@ function irwinHallCDF(n) {
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t += Math.pow(-1, k % 2) * binoms[k] * Math.pow(x - k, n);
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}
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return t / normalisingFactor;
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}
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};
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}
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function factorial(n) {
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