Merge pull request #267 from null-a/cauchy

Add Cauchy ERP.

src/erp.js

@@ -26,6 +26,7 @@ var _ = require('underscore');
 var util = require('./util');
 var assert = require('assert');
 
+var LOG_PI = 1.1447298858494002;
 var LOG_2PI = 1.8378770664093453;
 
 function ERP(obj) {
@@ -227,6 +228,20 @@ var multivariateGaussianERP = new ERP({
   score: multivariateGaussianScore
 });
 
+var cauchyERP = new ERP({
+  sample: function(params) {
+    var location = params[0];
+    var scale = params[1];
+    var u = util.random();
+    return location + scale * Math.tan(180 * (u - 0.5));
+  },
+  score: function(params, x) {
+    var location = params[0];
+    var scale = params[1];
+    return -LOG_PI - Math.log(scale) - Math.log(1 + Math.pow((x - location) / scale, 2));
+  }
+});
+
 var discreteERP = new ERP({
   sample: function(params) {
     return multinomialSample(params[0]);
@@ -695,6 +710,7 @@ module.exports = setErpNames({
   gaussianERP: gaussianERP,
   multinomialSample: multinomialSample,
   multivariateGaussianERP: multivariateGaussianERP,
+  cauchyERP: cauchyERP,
   poissonERP: poissonERP,
   randomIntegerERP: randomIntegerERP,
   uniformERP: uniformERP,

src/header.wppl

@@ -27,6 +27,10 @@ var multivariateGaussian = function(mu, cov) {
   return sample(multivariateGaussianERP, [mu, cov]);
 };
 
+var cauchy = function(location, scale) {
+  return sample(cauchyERP, [location, scale]);
+};
+
 var uniform = function(a, b) {
   return sample(uniformERP, [a, b]);
 };

tests/test-data/stochastic/expected/cauchy.json

@@ -0,0 +1,6 @@
+{
+  "hist": {
+    "true": 0.3743,
+    "false": 0.6257
+  }
+}

tests/test-data/stochastic/models/cauchy.wppl

@@ -0,0 +1,4 @@
+var model = function() {
+  var x = cauchy(2, 1.5);
+  return 1 < x && x <= 3;
+};

tests/test-inference.js

@@ -31,7 +31,8 @@ var tests = [
       beta: true,
       exponential: true,
       binomial: true,
-      poisson: true
+      poisson: true,
+      cauchy: true
     }
   },
   {