1var geometric = function(p) {
2  return flip(p) ? 1 + geometric(p) : 1
3}
4​
5geometric(0.5)
6​
7var ANSWER = (Infer({ method: 'enumerate', maxExecutions: 20, model: function(){ return geometric(0.5); } }));
8​

1var geometric = function(p) {
2  return flip(p) ? 1 : 1 + geometric(p);
3};
4​
5var ANSWER = Infer({ method: 'enumerate', maxExecutions: 20, model: function(){ return geometric(0.5); } });

1var binomial = function() {
2  var a = sample(Bernoulli({ p: 0.5 }))
3  var b = sample(Bernoulli({ p: 0.5 }))
4  var c = sample(Bernoulli({ p: 0.5 }))
5  return a + b + c
6}
7​
8var binomialDist = Infer({ model: binomial })
9​
10viz(binomialDist)
11​
12var ANSWER = (binomialDist);
13​

1var binomial = function() {
2  var a = flip(0.5) ? 1 : 0;
3  var b = flip(0.5) ? 1 : 0;
4  var c = flip(0.5) ? 1 : 0;
5  return a + b + c;
6};
7​
8var binomialDist = Infer({ model: binomial });
9​
10var ANSWER = binomialDist;

1var funnyBinomial = function(){
2  var a = sample(Bernoulli({ p: 0.5 }))
3  var b = sample(Bernoulli({ p: 0.5 }))
4  var c = sample(Bernoulli({ p: 0.5 }))
5  factor( (a || b) ? 0 : -2)
6  return a + b + c}
7​
8var funnyBinomialDist = Infer({ model: funnyBinomial })
9​
10viz(funnyBinomialDist)
11​
12var ANSWER = (funnyBinomialDist);
13​

1var funnyBinomial = function() {
2  var a = flip(0.5) ? 1 : 0;
3  var b = flip(0.5) ? 1 : 0;
4  var c = flip(0.5) ? 1 : 0;
5  factor((a || b) ? 0 : -2);
6  return a + b + c;
7};
8​
9var funnyBinomialDist = Infer({ model: funnyBinomial });
10​
11var ANSWER = funnyBinomialDist;

1var cpsFactorial = function(k, n) {
2  if (n == 0) {
3    k(1);
4  } else {
5    cpsFactorial(
6      function(x){ k(x * n) },
7      n - 1);
8  }
9}
10​
11cpsFactorial(print, 5)
12​
13var ANSWER = (cpsFactorial(function(x){return x;}, 5));
14​

1var cpsFactorial = function(k, n) {
2  if (n == 0) {
3    k(1);
4  } else {
5    cpsFactorial(function(result) {
6      k(result * n);
7    }, n - 1);
8  }
9};
10​
11var ANSWER = cpsFactorial(print, 5);

1var totalCpsFactorial = function(k, err, n) {
2  if (n < 0) {
3    err("cpsFactorial: n < 0!")
4  } else if (n == 0) {
5    k(1);
6  } else {
7    totalCpsFactorial(
8      function(x){ k(x * n) },
9      err,
10      n - 1);
11  }
12}
13​
14var printError = function(x){
15  print("Error: " + x);
16}
17​
18totalCpsFactorial(print, printError, 5)
19totalCpsFactorial(print, printError, -1)
20​
21var ANSWER = (totalCpsFactorial(function(x){return x;}, function(e){return 'err';}, -1));
22​

1var totalCpsFactorial = function(k, err, n) {
2  if (n < 0) {
3    return err("factorial undefined for negative numbers");
4  } else if (n === 0) {
5    return k(1);
6  } else {
7    return totalCpsFactorial(function(result) {
8      return k(n * result);
9    }, err, n - 1);
10  }
11};
12​
13var ANSWER = totalCpsFactorial(function(x){return x;}, function(e){return 'err';}, -1);

1var binomial = function(){
2    var a = sample(Bernoulli({ p: 0.1 }))
3    var b = sample(Bernoulli({ p: 0.9 }))
4    var c = sample(Bernoulli({ p: 0.1 }))
5    return a + b + c
6}
7​
8var maxExec = 10
9​
10viz(Infer({
11  model: binomial,
12  method: 'enumerate',
13  maxExecutions: maxExec, 
14  strategy: 'depthFirst'
15}));
16​
17viz(Infer({
18  model: binomial,
19  method: 'enumerate',
20  maxExecutions: maxExec, 
21  strategy: 'breadthFirst'
22}));
23​
24viz(Infer({
25  model: binomial,
26  method: 'enumerate',  
27  maxExecutions: maxExec, 
28  strategy: 'likelyFirst',
29}));
30​
31var ANSWER = ({depthFirst: Infer({model: binomial, method: 'enumerate', maxExecutions: 10, strategy: 'depthFirst'}), breadthFirst: Infer({model: binomial, method: 'enumerate', maxExecutions: 10, strategy: 'breadthFirst'}), likelyFirst: Infer({model: binomial, method: 'enumerate', maxExecutions: 10, strategy: 'likelyFirst'})});
32​

1var binomial = function() {
2  var a = sample(Bernoulli({p: 0.1})) ? 1 : 0;
3  var b = sample(Bernoulli({p: 0.9})) ? 1 : 0;
4  var c = sample(Bernoulli({p: 0.1})) ? 1 : 0;
5  return a + b + c;
6};
7​
8var depthFirstDist = Infer({ model: binomial, method: "enumerate", maxExecutions: 10, strategy: "depthFirst" });
9var breadthFirstDist = Infer({ model: binomial, method: "enumerate", maxExecutions: 10, strategy: "breadthFirst" });
10var likelyFirstDist = Infer({ model: binomial, method: "enumerate", maxExecutions: 10, strategy: "likelyFirst" });
11​
12var ANSWER = { depthFirst: depthFirstDist, breadthFirst: breadthFirstDist, likelyFirst: likelyFirstDist };

1​
2​
3var ANSWER = (Infer({model: function() { var transition = function(s) { return s ? flip(0.7) : flip(0.3); }; var observeState = function(s) { return s ? flip(0.9) : flip(0.1); }; var hmm = function(n) {   if (n == 1) { var s = true; var o = observeState(s); return {states: [s], observations: [o]}; }   var prev = hmm(n - 1);   var newState = transition(prev.states[prev.states.length - 1]);   var newObs = observeState(newState);   return {states: prev.states.concat([newState]), observations: prev.observations.concat([newObs])}; }; var r = hmm(3); factor(_.isEqual(r.observations, [false, false, false]) ? 0 : -Infinity); return r.states; }}));
4​

1var transition = function(s) {
2  return s ? flip(0.7) : flip(0.3);
3};
4​
5var observeState = function(s) {
6  return s ? flip(0.9) : flip(0.1);
7};
8​
9var hmm = function(n) {
10  if (n == 1) {
11    return {states: [true], observations: [observeState(true)]};
12  } else {
13    var prev = hmm(n - 1);
14    var newState = transition(prev.states[prev.states.length - 1]);
15    var newObs = observeState(newState);
16    return {states: prev.states.concat([newState]), observations: prev.observations.concat([newObs])};
17  }
18};
19​
20var ANSWER = Infer({model: function() {
21  var r = hmm(3);
22  factor(_.isEqual(r.observations, [false, false, false]) ? 0 : -Infinity);
23  return r.states;
24}});

1var pcfgTransition = function(symbol) {
2  var rules = {'start': {rhs: [['NP', 'V', 'NP'], ['NP', 'V']], probs: [0.4, 0.6]},
3               'NP': {rhs: [['A', 'NP'], ['N']], probs: [0.4, 0.6]} }
4  return rules[symbol].rhs[ discrete(rules[symbol].probs) ]
5}
6​
7var preTerminal = function(symbol) {
8  return symbol=='N' | symbol=='V' | symbol=='A'
9}
10​
11var terminal = function(symbol) {
12  var rules = {'N': {words: ['John', 'soup'], probs: [0.6, 0.4]},
13               'V': {words: ['loves', 'hates', 'runs'], probs: [0.3, 0.3, 0.4]},
14               'A': {words: ['tall', 'salty'], probs: [0.6, 0.4]} }
15  return rules[symbol].words[ discrete(rules[symbol].probs) ]
16}
17​
18​
19var pcfg = function(symbol) {
20  preTerminal(symbol) ? [terminal(symbol)] : expand(pcfgTransition(symbol))
21}
22​
23var expand = function(symbols) {
24  if(symbols.length==0) {
25    return []
26  } else {
27    var f = pcfg(symbols[0])
28    return f.concat(expand(symbols.slice(1)))
29  }
30}
31​
32var model = function(){
33  var y = pcfg("start")
34  factor(_.isEqual(y.slice(0,2), ["tall", "John"]) ? 0 : -Infinity) // yield starts with "tall John"
35  return y[2] ? y[2] : "" // distribution on next word?
36}
37​
38viz.table(Infer({ model, method: 'enumerate', maxExecutions: 20}))
39​
40var ANSWER = (Infer({ model, method: 'enumerate', maxExecutions: 20 }));
41​

1var rules = {
2  "start": {
3    expansions: [["NP","V","NP"], ["NP","V"]],
4    probs: [0.4, 0.6]
5  },
6  "NP": {
7    expansions: [["A","NP"], ["N"]],
8    probs: [0.4, 0.6]
9  },
10  "N": {
11    expansions: [["John"], ["soup"]],
12    probs: [0.6, 0.4]
13  },
14  "V": {
15    expansions: [["loves"], ["hates"], ["runs"]],
16    probs: [0.3, 0.3, 0.4]
17  },
18  "A": {
19    expansions: [["tall"], ["salty"]],
20    probs: [0.6, 0.4]
21  }
22};
23​
24var pcfgTransition = function(symbol) {
25  var idx = discrete(rules[symbol].probs);
26  return rules[symbol].expansions[idx];
27};
28​
29var preTerminal = function(symbol) {
30  return symbol === "N" || symbol === "V" || symbol === "A";
31};
32​
33var terminal = function(symbol) {
34  var idx = discrete(rules[symbol].probs);
35  return rules[symbol].expansions[idx][0];
36};
37​
38var pcfg = function(symbol) {
39  if (preTerminal(symbol)) {
40    return [terminal(symbol)];
41  } else {
42    var expansion = pcfgTransition(symbol);
43    return expand(expansion);
44  }
45};
46​
47var expand = function(symbols) {
48  if (symbols.length === 0) {
49    return [];
50  } else {
51    var first = symbols[0];
52    var rest = symbols.slice(1);
53    var firstYield = pcfg(first);
54    var restYield = expand(rest);
55    return firstYield.concat(restYield);
56  }
57};
58​
59var model = function() {
60  var y = pcfg("start");
61  factor(_.isEqual(y.slice(0, 2), ["tall", "John"]) ? 0 : -Infinity);
62  return y[2] ? y[2] : "";
63};
64​
65var ANSWER = Infer({ model: model, method: "enumerate", maxExecutions: 20 });

1///fold:
2var transition = function(s) {
3  return s ? flip(0.7) : flip(0.3)
4}
5​
6var observeState = function(s) {
7  return s ? flip(0.9) : flip(0.1)
8}
9​
10var trueObs = [false, false, false]
11///
12​
13var hmmRecur = function(n, states, observations){
14  var newState = transition(states[states.length-1])
15  var newObs = observeState(newState)
16  factor(newObs==trueObs[observations.length] ? 0 : -Infinity)
17  var newStates = states.concat([newState])
18  var newObservations = observations.concat([newObs])
19  return (n==1) ? { states: newStates, observations: newObservations } : 
20                  hmmRecur(n-1, newStates, newObservations)
21}
22​
23var hmm = function(n) {
24  return hmmRecur(n, [true], [])
25}
26​
27var model = function(){
28  var r = hmm(3)
29  return r.states
30}
31​
32viz.table(Infer({ model }))
33​
34var ANSWER = (Infer({ model }));
35​