[swift-users] Implementing a few statistics functions in Swift

[Nevin Brackett-Rozinsky]

…and of course I typoed the minus sign when switching things over. That
should be:

    private(set) var minimum: Number = Number.infinity
    private(set) var maximum: Number = -Number.infinity

Nevin


On Mon, Oct 10, 2016 at 4:02 PM, Nevin Brackett-Rozinsky <
nevin.brackettrozinsky at gmail.com> wrote:

> I rolled my own (rather simple) statistics struct. It had been using
> Double and Array, but I just went back and made it work generically with
> FloatingPoint and Sequence. Here’s what it looks like:
>
> struct Statistic<Number: FloatingPoint> {
>     private var ssqDev: Number = 0
>     private(set) var count: Number = 0
>     private(set) var average: Number = 0
>     private(set) var maximum: Number = Number.infinity
>     private(set) var minimum: Number = -Number.infinity
>
>     var variance: Number { return ssqDev / (count - 1) }
>     var standardDeviation: Number { return sqrt(variance) }
>
>     init() {}
>
>     init<T: Sequence> (values: T) where T.Iterator.Element == Number {
>         addValues(values)
>     }
>
>     mutating func addValues<T: Sequence> (_ vals: T) where
> T.Iterator.Element == Number {
>         for val in vals { addValue(val) }
>     }
>
>     mutating func addValue(_ value: Number) {
>         count += 1 as Number
>         let diff = value - average
>         let frac = diff / count
>         average += frac
>         ssqDev += diff * (diff - frac)
>         minimum = min(minimum, value)
>         maximum = max(maximum, value)
>     }
> }
>
>
> (Sorry for the lack of syntax highlighting—Gmail strips the formatting
> when I paste it.)
>
> Some notes:
>
> • The approach is to look at each data point once and keep the statistics
> correct for the numbers seen so far. This saves memory if the values are
> being computed or fetched, since you don’t need to store them. However it
> also means that the median cannot be found.
>
> • The calculation to update “average” and “ssqDev” is simplified from the
> online-algorithm
> <https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Online_algorithm>
> found on Wikipedia. (“ssqDev” stores the sum of squared deviations from the
> mean, which is just the sample variance times the count.)
>
> • If you want to ignore NaN’s, just add “if value.isNaN { return }” at the
> top of “addValue”.
>
> • The “as Number” coercion shouldn’t be necessary, but I was getting an
> “ambiguous use of +=” error without it.
>
> • All occurrences of “count” were originally “n”, which was private, and I
> had a computed “count” that just returned Int(n). But when I switched from
> “Double” to “Number: FloatingPoint” I lost the ability to write “Int(n)”.
>
>
> Nevin
>
>
>
> On Mon, Oct 10, 2016 at 1:13 PM, Harlan Haskins via swift-users <
> swift-users at swift.org> wrote:
>
>> Oh yeah, I'd love contributions and feedback! I'm essentially
>> implementing this as I learn things in stats 101 so it's probably woefully
>> inadequate. 😅
>>
>> -- Harlan
>>
>> On Oct 10, 2016, at 1:04 PM, Michael Ilseman <milseman at apple.com> wrote:
>>
>>
>> On Oct 8, 2016, at 11:29 AM, Georgios Moschovitis via swift-users <
>> swift-users at swift.org> wrote:
>>
>> Hey everyone,
>>
>> I would like to implement a few statistics functions in Swift (e.g.
>> variance, standardDeviation, etc) that are computed over a collection.
>>
>> I am aware of this library:
>>
>> https://github.com/evgenyneu/SigmaSwiftStatistics
>>
>> My problem is that it only supports Doubles and Arrays. Also the API
>> doesn’t look very ‘swifty' to me.
>>
>>
>> You might find this library to be more Swifty: https://github.com/har
>> lanhaskins/Probably
>>
>> It’s not as generic as possible nor has all the features you might need,
>> but the author is very responsive to feedback.
>>
>>
>> I am wondering how would someone implement such functionality in a more
>> generic way: to allow usage of multiple collections (even custom, e.g. a
>> RingBuffer) and multiple value types (e.g. Decimal, Double). Extra points
>> for being 'swifty'.
>>
>> Thanks in advance for any ideas.
>>
>> -g.
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>
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