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<title>AliasMethodDiscreteSampler</title>
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<div class="main-content" id="content" pageids="kmath-stat::space.kscience.kmath.samplers/AliasMethodDiscreteSampler///PointingToDeclaration//-443365019">
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<div class="breadcrumbs"><a href="../../index.html">kmath-stat</a>/<a href="../index.html">space.kscience.kmath.samplers</a>/<a href="index.html">AliasMethodDiscreteSampler</a></div>
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<h1 class="cover"><span>Alias</span><wbr><span>Method</span><wbr><span>Discrete</span><wbr><span>Sampler</span></h1>
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<div class="platform-hinted " data-platform-hinted="data-platform-hinted"><div class="content sourceset-depenent-content" data-active="" data-togglable=":kmath-stat:dokkaHtmlPartial/commonMain"><div class="symbol monospace">open class <a href="index.html">AliasMethodDiscreteSampler</a> : <a href="../../space.kscience.kmath.stat/-sampler/index.html">Sampler</a><<a href="https://kotlinlang.org/api/latest/jvm/stdlib/kotlin/-int/index.html">Int</a>> <span class="top-right-position"><span class="copy-icon"></span><div class="copy-popup-wrapper popup-to-left"><span class="copy-popup-icon"></span><span>Content copied to clipboard</span></div></span></div><p class="paragraph">Distribution sampler that uses the Alias method. It can be used to sample from n values each with an associated probability. This implementation is based on the detailed explanation of the alias method by Keith Schartz and implements Vose's algorithm.</p><p class="paragraph">Vose, M.D., A linear algorithm for generating random numbers with a given distribution, IEEE Transactions on Software Engineering, 17, 972-975, 1991. The algorithm will sample values in O(1) time after a pre-processing step of O(n) time.</p><p class="paragraph">The alias tables are constructed using fraction probabilities with an assumed denominator of 253. In the generic case sampling uses UniformRandomProvider.nextInt(int) and the upper 53-bits from UniformRandomProvider.nextLong().</p><p class="paragraph">Zero padding the input probabilities can be used to make more sampling more efficient. Any zero entry will always be aliased removing the requirement to compute a long. Increased sampling speed comes at the cost of increased storage space. The algorithm requires approximately 12 bytes of storage per input probability, that is n * 12 for size n. Zero-padding only requires 4 bytes of storage per padded value as the probability is known to be zero.</p><p class="paragraph">An optimisation is performed for small table sizes that are a power of 2. In this case the sampling uses 1 or 2 calls from UniformRandomProvider.nextInt() to generate up to 64-bits for creation of an 11-bit index and 53-bits for the long. This optimisation requires a generator with a high cycle length for the lower order bits.</p><p class="paragraph">Larger table sizes that are a power of 2 will benefit from fast algorithms for UniformRandomProvider.nextInt(int) that exploit the power of 2.</p><p class="paragraph">Based on Commons RNG implementation. See https://commons.apache.org/proper/commons-rng/commons-rng-sampling/apidocs/org/apache/commons/rng/sampling/distribution/AliasMethodDiscreteSampler.html.</p></div></div>
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<div class="tabs-section" tabs-section="tabs-section"><button class="section-tab" data-active="" data-togglable="Types">Types</button><button class="section-tab" data-togglable="Functions">Functions</button><button class="section-tab" data-togglable="Sources">Sources</button></div>
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<h2 class="">Types</h2>
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<div class="table" data-togglable="Types"><a data-name="-2146119335%2FClasslikes%2F-443365019" anchor-label="Companion" id="-2146119335%2FClasslikes%2F-443365019" data-filterable-set=":kmath-stat:dokkaHtmlPartial/commonMain"></a>
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<div class=""><span class="inline-flex"><a href="-companion/index.html">Companion</a><span class="anchor-wrapper"><span class="anchor-icon" pointing-to="-2146119335%2FClasslikes%2F-443365019"></span>
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<h2 class="">Functions</h2>
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<div class="table" data-togglable="Functions"><a data-name="829807022%2FFunctions%2F-443365019" anchor-label="AliasMethodDiscreteSampler" id="829807022%2FFunctions%2F-443365019" data-filterable-set=":kmath-stat:dokkaHtmlPartial/commonMain"></a>
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<div class=""><span class="inline-flex"><a href="-alias-method-discrete-sampler.html">AliasMethodDiscreteSampler</a><span class="anchor-wrapper"><span class="anchor-icon" pointing-to="829807022%2FFunctions%2F-443365019"></span>
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<div class="platform-tag common-like">common</div>
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<div class="title"><div class="divergent-group" data-filterable-current=":kmath-stat:dokkaHtmlPartial/commonMain" data-filterable-set=":kmath-stat:dokkaHtmlPartial/commonMain"><div class="with-platform-tags"><span class="pull-right"></span></div>
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<div class="platform-hinted " data-platform-hinted="data-platform-hinted"><div class="content sourceset-depenent-content" data-active="" data-togglable=":kmath-stat:dokkaHtmlPartial/commonMain"><div class="symbol monospace">fun <a href="-alias-method-discrete-sampler.html">AliasMethodDiscreteSampler</a>(probabilities: <a href="https://kotlinlang.org/api/latest/jvm/stdlib/kotlin/-double-array/index.html">DoubleArray</a>, alpha: <a href="https://kotlinlang.org/api/latest/jvm/stdlib/kotlin/-int/index.html">Int</a> = DEFAULT_ALPHA): <a href="../../space.kscience.kmath.stat/-sampler/index.html">Sampler</a><<a href="https://kotlinlang.org/api/latest/jvm/stdlib/kotlin/-int/index.html">Int</a>><span class="top-right-position"><span class="copy-icon"></span><div class="copy-popup-wrapper popup-to-left"><span class="copy-popup-icon"></span><span>Content copied to clipboard</span></div></span></div></div></div>
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<a data-name="13728422%2FFunctions%2F-443365019" anchor-label="sample" id="13728422%2FFunctions%2F-443365019" data-filterable-set=":kmath-stat:dokkaHtmlPartial/commonMain"></a>
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<div class=""><span class="inline-flex"><a href="sample.html">sample</a><span class="anchor-wrapper"><span class="anchor-icon" pointing-to="13728422%2FFunctions%2F-443365019"></span>
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<div class="platform-tag common-like">common</div>
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<div class="title"><div class="divergent-group" data-filterable-current=":kmath-stat:dokkaHtmlPartial/commonMain" data-filterable-set=":kmath-stat:dokkaHtmlPartial/commonMain"><div class="with-platform-tags"><span class="pull-right"></span></div>
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<div class="platform-hinted " data-platform-hinted="data-platform-hinted"><div class="content sourceset-depenent-content" data-active="" data-togglable=":kmath-stat:dokkaHtmlPartial/commonMain"><div class="symbol monospace">open override fun <a href="sample.html">sample</a>(generator: <a href="../../space.kscience.kmath.stat/-random-generator/index.html">RandomGenerator</a>): <a href="../../../kmath-coroutines/space.kscience.kmath.chains/-chain/index.html">Chain</a><<a href="https://kotlinlang.org/api/latest/jvm/stdlib/kotlin/-int/index.html">Int</a>><span class="top-right-position"><span class="copy-icon"></span><div class="copy-popup-wrapper popup-to-left"><span class="copy-popup-icon"></span><span>Content copied to clipboard</span></div></span></div></div></div>
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<a data-name="13728422%2FFunctions%2F-443365019" anchor-label="sample" id="13728422%2FFunctions%2F-443365019" data-filterable-set=":kmath-stat:dokkaHtmlPartial/commonMain"></a><div class="brief "><a data-name="13728422%2FFunctions%2F-443365019" anchor-label="sample" id="13728422%2FFunctions%2F-443365019" data-filterable-set=":kmath-stat:dokkaHtmlPartial/commonMain"></a>Generates a chain of samples.</div></div>
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<a data-name="-401020964%2FFunctions%2F-443365019" anchor-label="toString" id="-401020964%2FFunctions%2F-443365019" data-filterable-set=":kmath-stat:dokkaHtmlPartial/commonMain"></a>
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<div class=""><span class="inline-flex"><a href="to-string.html">toString</a><span class="anchor-wrapper"><span class="anchor-icon" pointing-to="-401020964%2FFunctions%2F-443365019"></span>
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<div class="title"><div class="divergent-group" data-filterable-current=":kmath-stat:dokkaHtmlPartial/commonMain" data-filterable-set=":kmath-stat:dokkaHtmlPartial/commonMain"><div class="with-platform-tags"><span class="pull-right"></span></div>
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<div class="platform-hinted " data-platform-hinted="data-platform-hinted"><div class="content sourceset-depenent-content" data-active="" data-togglable=":kmath-stat:dokkaHtmlPartial/commonMain"><div class="symbol monospace">open override fun <a href="to-string.html">toString</a>(): <a href="https://kotlinlang.org/api/latest/jvm/stdlib/kotlin/-string/index.html">String</a><span class="top-right-position"><span class="copy-icon"></span><div class="copy-popup-wrapper popup-to-left"><span class="copy-popup-icon"></span><span>Content copied to clipboard</span></div></span></div></div></div>
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<h2 class="">Sources</h2>
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<div class="table" data-togglable="Sources"><a data-name="2039416215%2FSource%2F-443365019" anchor-label="https://github.com/mipt-npm/kmath/tree/master/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AliasMethodDiscreteSampler.kt#L17" id="2039416215%2FSource%2F-443365019" data-filterable-set=":kmath-stat:dokkaHtmlPartial/commonMain"></a>
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<div class=""><span class="inline-flex"><a href="https://github.com/mipt-npm/kmath/tree/master/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AliasMethodDiscreteSampler.kt#L17">common source</a><span class="anchor-wrapper"><span class="anchor-icon" pointing-to="2039416215%2FSource%2F-443365019"></span>
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