Merge branch 'dev'

.gitignore

@@ -7,6 +7,6 @@ bundle/
 docs/_build
 docs/_static
 docs/_templates
-src/erp.js
+src/dists.js
 src/inference/enumerate.js
-src/aggregation/distribution.js
+src/aggregation/ScoreAggregator.js

Gruntfile.js

@@ -16,7 +16,7 @@ var jslintSettings = {
     src: [
       'Gruntfile.js',
       'src/header.wppl',
-      'src/**/!(erp|enumerate|distribution).js'
+      'src/**/!(dists|enumerate|ScoreAggregator).js'
     ]
   },
   test: {
@@ -140,4 +140,9 @@ module.exports = function(grunt) {
       throw e;
     }
   });
+
+  grunt.registerTask('generate-docs', 'Generate documentation.', function() {
+    var output = child_process.execSync('scripts/distributionDocs > docs/distributions.rst');
+    grunt.log.writeln(output);
+  });
 };

docs/development/npm.rst

@@ -17,5 +17,5 @@ Updating the npm package
 
     git push origin dev
     git push origin master
-    git push origin v0.0.1  // again, use version printed by "npm version" command above
+    git push origin v0.0.1  // use version printed by "npm version" command above
     npm publish

docs/distributions.rst

@@ -0,0 +1,107 @@
+Distributions
+=============
+
+.. js:function:: Bernoulli({p: ...})
+
+  * p: *probability of true*
+
+  Distribution on {true,false}
+
+.. js:function:: Beta({a: ..., b: ...})
+
+  * a
+  * b
+
+.. js:function:: Binomial({p: ..., n: ...})
+
+  * p: *success probability*
+  * n: *number of trials*
+
+  Distribution over the number of successes for n independent ``Bernoulli({p: p})`` trials
+
+.. js:function:: Categorical({ps: ..., vs: ...})
+
+  * ps: *array of probabilities*
+  * vs: *support*
+
+  Distribution over elements of vs with P(vs[i]) = ps[i]
+
+.. js:function:: Cauchy({location: ..., scale: ...})
+
+  * location
+  * scale
+
+.. js:function:: Delta({v: ...})
+
+  * v: *support element*
+
+  Discrete distribution that assigns probability one to the single element in its support. This is only useful in special circumstances as sampling from ``Delta({v: val})`` can be replaced with ``val`` itself. Furthermore, a ``Delta`` distribution parameterized by a random choice should not be used with MCMC based inference, as doing so produces incorrect results.
+
+.. js:function:: Dirichlet({alpha: ...})
+
+  * alpha: *array of concentration parameters*
+
+.. js:function:: DirichletDrift({alpha: ...})
+
+  * alpha: *array of concentration parameters*
+
+.. js:function:: Discrete({ps: ...})
+
+  * ps: *array of probabilities*
+
+  Distribution on {0,1,...,ps.length-1} with P(i) proportional to ps[i]
+
+.. js:function:: Exponential({a: ...})
+
+  * a: *rate*
+
+.. js:function:: Gamma({shape: ..., scale: ...})
+
+  * shape
+  * scale
+
+.. js:function:: Gaussian({mu: ..., sigma: ...})
+
+  * mu: *mean*
+  * sigma: *standard deviation*
+
+.. js:function:: GaussianDrift({mu: ..., sigma: ...})
+
+  * mu: *mean*
+  * sigma: *standard deviation*
+
+.. js:function:: Multinomial({ps: ..., n: ...})
+
+  * ps: *probabilities*
+  * n: *number of trials*
+
+  Distribution over counts for n independent ``Discrete({ps: ps})`` trials
+
+.. js:function:: MultivariateGaussian({mu: ..., cov: ...})
+
+  * mu: *mean vector*
+  * cov: *covariance matrix*
+
+.. js:function:: Poisson({mu: ...})
+
+  * mu
+
+.. js:function:: RandomInteger({n: ...})
+
+  * n
+
+  Uniform distribution on {0,1,...,n-1}
+
+.. js:function:: Uniform({a: ..., b: ...})
+
+  * a
+  * b
+
+  Continuous uniform distribution on [a, b]
+
+.. js:function:: UniformDrift({a: ..., b: ..., r: ...})
+
+  * a
+  * b
+  * r: *drift kernel radius*
+

docs/index.rst

@@ -9,6 +9,7 @@ Contents:
    quickstart
    usage
    inference
+   distributions
    debugging
    packages
    development/index