{"id":4933,"date":"2007-12-18T18:09:00","date_gmt":"2007-12-18T18:09:00","guid":{"rendered":"https:\/\/blogs.msdn.microsoft.com\/vbteam\/2007\/12\/18\/linq-cookbook-recipe-12-calculate-the-standard-deviation-doug-rothaus\/"},"modified":"2024-07-05T14:35:45","modified_gmt":"2024-07-05T21:35:45","slug":"linq-cookbook-recipe-12-calculate-the-standard-deviation-doug-rothaus","status":"publish","type":"post","link":"https:\/\/devblogs.microsoft.com\/vbteam\/linq-cookbook-recipe-12-calculate-the-standard-deviation-doug-rothaus\/","title":{"rendered":"LINQ Cookbook, Recipe 12: Calculate the Standard Deviation (Doug Rothaus)"},"content":{"rendered":"

Ingredients:<\/p>\n

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·         <\/span><\/span><\/span>Visual Studio 2008 (Beta2 or Higher)<\/span><\/p>\n

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Categories:<\/span><\/b> LINQ to Objects<\/p>\n

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Introduction:<\/p>\n

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LINQ Cookbook, Recipe 11<\/font><\/a> showed how you can use LINQ queries to perform calculations on sets of data using a set of standard aggregate functions such as Average<\/b>, and Sum<\/b>. In this recipe, you will learn how to add an extension method so that you can include your own custom aggregate function in a LINQ query.<\/p>\n

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This recipe adds two <\/font>extension methods<\/font><\/a>: StDev (standard deviation) and StDevP (standard deviation for the entire population). Because the extension methods are added to the IEnumerable(Of T)<\/b> type, you can use the custom aggregate functions in the Into<\/b> clause of an Aggregate<\/b>, Group By<\/b>, or Group Join<\/b> query clause. Notice that there are two overloads of each extension method: one that takes input values of type IEnumerable(Of Double)<\/b>, and another that takes input values of type IEnumerable(Of T)<\/b>. This enables you to call the custom aggregate functions whether your LINQ query returns a collection of type Double<\/b>, or any other numeric type. The overload that takes input values of type IEnumerable(Of T)<\/b> uses the Func(Of T, Double)<\/b> <\/font>lambda expression<\/font><\/a> to project a the numeric values as the corresponding values of type Double<\/b> before calculating the standard deviation. When calculating the standard deviation for values of type Double<\/b>, you can simply call the StDev() or StDevP() overloads. When calculating the standard deviation for values of numeric types other than Double<\/b>, you need to pass the value to the StDev(value) or StDevP(value) overloads to ensure that the value is projected as type Double<\/b>.<\/p>\n

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Instructions:<\/p>\n

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·         <\/span><\/span><\/span>Create a Console Application.<\/p>\n

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·         <\/span><\/span><\/span>After the <\/font><\/span>End Module<\/span> statement of the default <\/font><\/span>Module1<\/span> module, add the following class, which contains both the StDev and StDevP functions.<\/p>\n

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Class<\/span> StatisticalFunctions<\/p>\n

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    <\/span>Public<\/span> Shared<\/span> Function<\/span> StDev(ByVal<\/span> values As<\/span> Double<\/span>()) As<\/span> Double<\/p>\n

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        <\/span>Return<\/span> CalculateStDev(values, False<\/span>)<\/p>\n

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    <\/span>End<\/span> Function<\/p>\n

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    <\/span>Public<\/span> Shared<\/span> Function<\/span> StDevP(ByVal<\/span> values As<\/span> Double<\/span>()) As<\/span> Double<\/p>\n

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        <\/span>Return<\/span> CalculateStDev(values, True<\/span>)<\/p>\n

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    <\/span>End<\/span> Function<\/p>\n

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    <\/span>Private<\/span> Shared<\/span> Function<\/span> CalculateStDev(ByVal<\/span> values As<\/span> Double<\/span>(), _<\/p>\n

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                                           <\/span>ByVal<\/span> entirePopulation As<\/span> Boolean<\/span>) As<\/span> Double<\/p>\n

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        <\/span>Dim<\/span> count As<\/span> Integer<\/span> = 0<\/p>\n

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        <\/span>Dim<\/span> var As<\/span> Double<\/span> = 0<\/p>\n

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        <\/span>Dim<\/span> prec As<\/span> Double<\/span> = 0<\/p>\n

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        <\/span>Dim<\/span> dSum As<\/span> Double<\/span> = 0<\/p>\n

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        <\/span>Dim<\/span> sqrSum As<\/span> Double<\/span> = 0<\/p>\n

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        <\/span>Dim<\/span> adjustment As<\/span> Integer<\/span> = 1<\/p>\n

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        <\/span>If<\/span> entirePopulation Then<\/span> adjustment = 0<\/p>\n

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        <\/span>For<\/span> Each<\/span> val As<\/span> Double<\/span> In<\/span> values<\/p>\n

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            <\/span>dSum += val<\/p>\n

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            <\/span>sqrSum += val * val<\/p>\n

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            <\/span>count += 1<\/p>\n

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        <\/span>Next<\/p>\n

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        <\/span>If<\/span> count > 1 Then<\/p>\n

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            <\/span>var = count * sqrSum – (dSum * dSum)<\/p>\n

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            <\/span>prec = var \/ (dSum * dSum)<\/p>\n

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            <\/span>‘ Double is only guaranteed for 15 digits. A difference <\/p>\n

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            <\/span>‘ with a result less than 0.000000000000001 will be considered zero.<\/p>\n

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            <\/span>If<\/span> prec < 0.000000000000001 OrElse<\/span> var < 0 Then<\/p>\n

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                <\/span>var = 0<\/p>\n

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            <\/span>Else<\/p>\n

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                <\/span>var = var \/ (count * (count – adjustment))<\/p>\n

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            <\/span>End<\/span> If<\/p>\n

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            <\/span>Return<\/span> Math.Sqrt(var)<\/p>\n

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        <\/span>End<\/span> If<\/p>\n

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        <\/span>Return<\/span> No\nthing<\/p>\n

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    <\/span>End<\/span> Function<\/p>\n

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End<\/span> Class<\/span><\/span><\/p>\n

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·         <\/span><\/span><\/span>After the StatisticalFunctions class, add the following module to add the extension methods to IEnumerable<\/b> to calculate the standard deviation for both IEnumerable(Of Double)<\/b> and IEnumerable(Of T)<\/b>.<\/p>\n

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Module<\/span> StatisticalAggregates<\/p>\n

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    <\/span>‘ Calculate the stdev value for a collection of type Double.<\/p>\n

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    <\/span><Extension()> _<\/p>\n

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    <\/span>Function<\/span> StDev(ByVal<\/span> stDevAggregate As<\/span> IEnumerable(Of<\/span> Double<\/span>)) As<\/span> Double<\/p>\n

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        <\/span>Return<\/span> StatisticalFunctions.StDev(stDevAggregate.ToArray())<\/p>\n

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    <\/span>End<\/span> Function<\/p>\n

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    <\/span>‘ Project the collection of generic items as type Double and calculate the stdev value. <\/p>\n

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    <\/span><Extension()> _<\/p>\n

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    <\/span>Function<\/span> StDev(Of<\/span> T)(ByVal<\/span> stDevAggregate As<\/span> IEnumerable(Of<\/span> T), _<\/p>\n

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                         <\/span>ByVal<\/span> selector As<\/span> Func(Of<\/span> T, Double<\/span>)) As<\/span> Double<\/p>\n

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        <\/span>Dim<\/span> values = (From<\/span> element In<\/span> stDevAggregate Select<\/span> selector(element)).ToArray()<\/p>\n

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        <\/span>Return<\/span> StatisticalFunctions.StDev(values)<\/p>\n

<\/span><\/p><\/p>\n","protected":false},"excerpt":{"rendered":"

Ingredients: ·         Visual Studio 2008 (Beta2 or Higher)   Categories: LINQ to Objects   Introduction: LINQ Cookbook, Recipe 11 showed how you can use LINQ queries to perform calculations on sets of data using a set of standard aggregate functions such as Average, and Sum. In this recipe, you will learn how to add an […]<\/p>\n","protected":false},"author":260,"featured_media":8818,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[192,195],"tags":[59,93,94,117,166],"class_list":["post-4933","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-featured","category-visual-basic","tag-doug-rothaus","tag-linq-cookbook","tag-linqvb9","tag-orcas","tag-vb2008"],"acf":[],"blog_post_summary":"

Ingredients: ·         Visual Studio 2008 (Beta2 or Higher)   Categories: LINQ to Objects   Introduction: LINQ Cookbook, Recipe 11 showed how you can use LINQ queries to perform calculations on sets of data using a set of standard aggregate functions such as Average, and Sum. In this recipe, you will learn how to add an […]<\/p>\n","_links":{"self":[{"href":"https:\/\/devblogs.microsoft.com\/vbteam\/wp-json\/wp\/v2\/posts\/4933","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/devblogs.microsoft.com\/vbteam\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/devblogs.microsoft.com\/vbteam\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/vbteam\/wp-json\/wp\/v2\/users\/260"}],"replies":[{"embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/vbteam\/wp-json\/wp\/v2\/comments?post=4933"}],"version-history":[{"count":0,"href":"https:\/\/devblogs.microsoft.com\/vbteam\/wp-json\/wp\/v2\/posts\/4933\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/vbteam\/wp-json\/wp\/v2\/media\/8818"}],"wp:attachment":[{"href":"https:\/\/devblogs.microsoft.com\/vbteam\/wp-json\/wp\/v2\/media?parent=4933"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/vbteam\/wp-json\/wp\/v2\/categories?post=4933"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/vbteam\/wp-json\/wp\/v2\/tags?post=4933"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}