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概率编程——Figaro的基础示例

0. 导包

import com.cra.figaro.algorithm.factored.VariableEliminationimport com.cra.figaro.algorithm.sampling.Importanceimport com.cra.figaro.language._import com.cra.figaro.library.atomic.continuous.{
   Normal, Uniform}import com.cra.figaro.library.atomic.discrete.Binomialimport com.cra.figaro.library.compound.If

1. 原子元素

• 离散型
  • Flip

  val sunnyToday = Flip(0.2)println(VariableElimination.probability(sunnyToday, true))

  • Select

  val language = Select(  0.5 -> "Java",  0.3 -> "Scala",  0.2 -> "Python")println(VariableElimination.probability(language, "Scala"))

  • Binomial

  val numSunnyDayInWeek = Binomial(7, 0.5)println(VariableElimination.probability(numSunnyDayInWeek, 3))

• 连续型
  • Normal 正态分布

  val temperature = Normal(40, 100)val greaterThan50 = (d: Double) => d > 50println(Importance.probability(temperature, greaterThan50))

  • Uniform 连续均匀分布

  val temperature2 = Uniform(10, 81)println(Importance.probability(temperature2, greaterThan50))

2. 复合元素

• If

  val sunnyToday = Flip(0.2)val greetingToday = If(sunnyToday,  Select(0.6 -> "Hello World!", 0.4 -> "Howdy, universe!"),  Select(0.2 -> "Hello World!", 0.8 -> "Oh no, not again!"))println(VariableElimination.probability(greetingToday, "Hello World!"))sunnyToday.observe(true)println(VariableElimination.probability(greetingToday, "Hello World!"))

• Dist

  val goodMood = Dist(  0.2 -> Flip(0.6),  0.8 -> Flip(0.2))println(VariableElimination.probability(goodMood, true))

• 原子复合

  val sunnyTodayProbability = Uniform(0, 0.6)val sunnyToday2 = Flip(sunnyTodayProbability)println(Importance.probability(sunnyToday2, true))val tempMean = Normal(40, 36)val temperature = Normal(tempMean, 100)println(Importance.probability(temperature, (d: Double) => d > 50))

• Apply

  val sunnyDaysInMonth = Binomial(30, 0.2)val getQuality = (i: Int) => if (i > 10) "good" else if (i > 5) "average" else "poor"val monthQuality = Apply(sunnyDaysInMonth, getQuality)println(VariableElimination.probability(monthQuality, "good"))val teamWinsInMonth = Binomial(5, 0.4)val monthQuality2 = Apply(sunnyDaysInMonth, teamWinsInMonth,  (days: Int, wins: Int) => {
           val x = days * wins    if (x > 20) "good" else if (x > 10) "average" else "poor"  })println(VariableElimination.probability(monthQuality2, "good"))

• Chain

  val goodMood2 = Chain(monthQuality,  (s: String) =>    if (s == "good") Flip(0.9)    else if (s == "average") Flip(0.6)    else Flip(0.1))println(VariableElimination.probability(goodMood2, true))val sunnyToday3 = Flip(0.2)val goodMood3 = Chain(monthQuality, sunnyToday3,  (quality: String, sunny: Boolean) => {
           (quality, sunny) match {
             case ("good", true) => Flip(0.9)      case ("average", true) => Flip(0.7)      case (_, true) => Flip(0.4)      case ("good", false) => Flip(0.6)      case ("average", false) => Flip(0.3)      case (_, false) => Flip(0.05)    }  })println(VariableElimination.probability(goodMood3, true))

3. 条件与约束

• 条件

  val sunntDayInMonth = Binomial(30, 0.2)val monthQuality = Apply(sunntDayInMonth,  (i: Int) => if (i > 10) "good" else if (i > 5) "average" else "poor")val goodMood = Chain(monthQuality,  (s: String) => {
           if (s == "good") Flip(0.9)    else if (s == "average") Flip(0.6)    else Flip(0.1)  })println(VariableElimination.probability(goodMood, true))// 设置条件，会清楚之前所有的条件sunntDayInMonth.setCondition((i: Int) => i > 8)println(VariableElimination.probability(goodMood, true))// 添加条件sunntDayInMonth.addCondition((i: Int) => i % 3 == 2)println(VariableElimination.probability(goodMood, true))// 移除条件sunntDayInMonth.removeConditions()println(VariableElimination.probability(goodMood, true))

• 约束

  goodMood.setConstraint((b: Boolean) => if (b) 0.5 else 1.0)println(VariableElimination.probability(goodMood, true))val result1 = Flip(0.4)val result2 = Flip(0.4)val result3 = Flip(0.4)val allWins = Apply(result1, result2, result3,  (w1: Boolean, w2: Boolean, w3: Boolean) => w1 && w2 && w3)println(VariableElimination.probability(allWins, true))def makeStreaky(r1: Element[Boolean], r2: Element[Boolean]): Unit = {
         val pair = Apply(r1, r2, (b1: Boolean, b2: Boolean) => (b1, b2))  pair.setConstraint((bb: (Boolean, Boolean)) => if (bb._1 == bb._2) 1.0 else 0.5)}makeStreaky(result1, result2)makeStreaky(result2, result3)println(VariableElimination.probability(allWins, true))

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