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sritchiesritchie
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feat: add kixi for cljc stats
1 parent e62668e commit 2beadb6

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Lines changed: 213 additions & 9 deletions

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‎deps.edn‎

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{:paths ["src" "resources"]
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:deps
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{org.apache.commons/commons-math3 {:mvn/version "3.6.1"}
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{kixi/stats {:mvn/version "0.5.5"}
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org.apache.commons/commons-math3 {:mvn/version "3.6.1"}
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org.clojure/clojure {:mvn/version "1.11.1"}}
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:aliases

‎src/gen/distribution/commons_math.clj‎

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0 false
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1 true)))))
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(defn beta-distribution [^double alpha ^double beta]
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(BetaDistribution. (rng) alpha beta))
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(defn beta-distribution
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([] (beta-distribution 1.0 1.0))
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([^double alpha ^double beta]
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(BetaDistribution. (rng) alpha beta)))
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(defn gamma-distribution [^double shape ^double scale]
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(GammaDistribution. (rng) shape scale))
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(defn normal-distribution [^double mean ^double sd]
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(NormalDistribution. (rng) mean sd))
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(defn normal-distribution
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([] (normal-distribution 0.0 1.0))
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([^double mean ^double sd]
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(NormalDistribution. (rng) mean sd)))
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(defn uniform-distribution [^double low ^double high]
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(UniformRealDistribution. (rng) low high))
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(defn uniform-distribution
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([] (uniform-distribution 0.0 1.0))
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([^double low ^double high]
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(UniformRealDistribution. (rng) low high)))
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(defn uniform-discrete-distribution [low high]
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(UniformIntegerDistribution. low high))
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(UniformIntegerDistribution. (rng) low high))
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(defn categorical-distribution [probabilities]
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(let [n (count probabilities)
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;; ## Primitive generative functions
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(def bernoulli
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"Generative function... TODO flesh out."
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(d/->GenerativeFn bernoulli-distribution))
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(def beta

‎src/gen/distribution/kixi.clj‎

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(ns gen.distribution.kixi
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(:require [gen.distribution :as d]
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[gen.distribution.math.log-likelihood :as ll]
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[kixi.stats.distribution :as k])
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(:import (kixi.stats.distribution Bernoulli Cauchy
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Exponential Beta
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Gamma Normal Uniform)))
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;; ## Kixi.stats protocol implementations
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;;
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;; NOTE: If we want to seed the PRNG here, the right way to do it is to create
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;; wrapper types that hold a kixi distribution instance and an RNG. Then,
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;; instead of `draw`, we can call `sample-1` with the distribution and RNG.
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(extend-type Bernoulli
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d/Sample
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(sample [this] (k/draw this))
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d/LogPDF
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(logpdf [this v]
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(ll/bernoulli (.-p this) v)))
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(extend-type Beta
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d/Sample
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(sample [this] (k/draw this))
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d/LogPDF
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(logpdf [this v]
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(ll/beta (.-alpha this)
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(.-beta this)
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v)))
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(extend-type Cauchy
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d/Sample
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(sample [this] (k/draw this))
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d/LogPDF
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(logpdf [this v]
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(ll/cauchy (.-location this)
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(.-scale this)
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v)))
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(extend-type Exponential
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d/Sample
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(sample [this] (k/draw this))
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d/LogPDF
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(logpdf [this v]
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(ll/exponential (.-rate this) v)))
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(extend-type Uniform
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d/Sample
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(sample [this] (k/draw this))
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d/LogPDF
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(logpdf [this v]
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(let [min (.-a this)
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max (.-b this)]
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(ll/uniform min max v))))
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(extend-type Gamma
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d/Sample
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(sample [this] (k/draw this))
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d/LogPDF
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(logpdf [this v]
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(ll/gamma (.-shape this)
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(.-scale this)
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v)))
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(extend-type Normal
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d/Sample
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(sample [this] (k/draw this))
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d/LogPDF
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(logpdf [this v]
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(ll/gaussian (.-mu this)
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(.-sd this)
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v)))
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;; ## Primitive probability distributions
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(defn bernoulli-distribution
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([] (bernoulli-distribution 0.5))
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([p] (k/bernoulli {:p p})))
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(defn beta-distribution
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([] (beta-distribution 1.0 1.0))
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([alpha beta]
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(k/beta {:alpha alpha :beta beta})))
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(defn cauchy-distribution [location scale]
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(k/cauchy {:location location :scale scale}))
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(defn exponential-distribution [rate]
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(k/exponential {:rate rate}))
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(defn uniform-distribution
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([] (uniform-distribution 0.0 1.0))
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([lo hi]
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(k/uniform {:a lo :b hi})))
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(defn normal-distribution
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([] (normal-distribution 0.0 1.0))
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([mu sigma]
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(k/normal {:mu mu :sd sigma})))
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(defn gamma-distribution [shape scale]
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(k/gamma {:shape shape :scale scale}))
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;; ## Primitive generative functions
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(def bernoulli
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(d/->GenerativeFn bernoulli-distribution))
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(def beta
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(d/->GenerativeFn beta-distribution))
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(def cauchy
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(d/->GenerativeFn cauchy-distribution))
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(def exponential
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(d/->GenerativeFn exponential-distribution))
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(def uniform
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(d/->GenerativeFn uniform-distribution))
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(def normal
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(d/->GenerativeFn normal-distribution))
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(def gamma
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(d/->GenerativeFn gamma-distribution))

‎test/gen/distribution/kixi_test.clj‎

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(ns gen.distribution.kixi-test
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(:require [clojure.math :as math]
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[clojure.test :refer [deftest is]]
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[gen]
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[gen.choice-map]
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[gen.diff :as diff]
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[gen.distribution.kixi :as d]
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[gen.generative-function :as gf]
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[gen.trace :as trace]))
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(deftest bernoulli-call-no-args
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(is (boolean? (d/bernoulli))))
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(deftest bernoulli-call-args
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(is (boolean? (d/bernoulli 0.5))))
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(deftest bernoulli-gf
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(is (= d/bernoulli (trace/gf (gf/simulate d/bernoulli [])))))
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(deftest bernoulli-args
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(is (= [0.5] (trace/args (gf/simulate d/bernoulli [0.5])))))
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(deftest bernoulli-retval
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(is (boolean? (trace/retval (gf/simulate d/bernoulli [0.5])))))
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(deftest bernoulli-choices-noargs
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(trace/choices (gf/simulate d/bernoulli [])))
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(deftest bernoulli-update-weight
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(is (= 1.0
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(-> (gf/generate d/bernoulli [0.3] #gen/choice true)
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(:trace)
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(trace/update #gen/choice true)
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(:weight)
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(math/exp))))
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(is (= (/ 0.7 0.3)
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(-> (gf/generate d/bernoulli [0.3] #gen/choice true)
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(:trace)
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(trace/update #gen/choice false)
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(:weight)
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(math/exp)))))
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(deftest bernoulli-update-discard
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(is (nil?
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(-> (gf/generate d/bernoulli [0.3] #gen/choice true)
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(:trace)
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(trace/update nil)
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(:discard))))
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(is (= #gen/choice true
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(-> (gf/generate d/bernoulli [0.3] #gen/choice true)
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(:trace)
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(trace/update #gen/choice false)
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(:discard)))))
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(deftest bernoulli-update-change
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(is (= diff/unknown-change
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(-> (gf/generate d/bernoulli [0.3] #gen/choice true)
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(:trace)
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(trace/update nil)
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(:change))))
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(is (= diff/unknown-change
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(-> (gf/generate d/bernoulli [0.3] #gen/choice true)
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(:trace)
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(trace/update #gen/choice false)
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(:change)))))

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