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* Deprecate sums * Update changelog.md * Update lib/std/sums.nim * log * format * remove * Update changelog.md Co-authored-by: sandytypical <43030857+xflywind@users.noreply.github.com>
81 lines
2.3 KiB
Nim
81 lines
2.3 KiB
Nim
#
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#
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# Nim's Runtime Library
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# (c) Copyright 2019 b3liever
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#
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# See the file "copying.txt", included in this
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# distribution, for details about the copyright.
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## Accurate summation functions.
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{.deprecated: "use the nimble package `sums` instead.".}
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runnableExamples:
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import std/math
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template `~=`(x, y: float): bool = abs(x - y) < 1e-4
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let
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n = 1_000_000
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first = 1e10
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small = 0.1
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var data = @[first]
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for _ in 1 .. n:
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data.add(small)
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let result = first + small * n.float
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doAssert abs(sum(data) - result) > 0.3
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doAssert sumKbn(data) ~= result
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doAssert sumPairs(data) ~= result
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## See also
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## ========
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## * `math module <math.html>`_ for a standard `sum proc <math.html#sum,openArray[T]>`_
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func sumKbn*[T](x: openArray[T]): T =
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## Kahan-Babuška-Neumaier summation: O(1) error growth, at the expense
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## of a considerable increase in computational cost.
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##
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## See:
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## * https://en.wikipedia.org/wiki/Kahan_summation_algorithm#Further_enhancements
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if len(x) == 0: return
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var sum = x[0]
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var c = T(0)
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for i in 1 ..< len(x):
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let xi = x[i]
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let t = sum + xi
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if abs(sum) >= abs(xi):
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c += (sum - t) + xi
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else:
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c += (xi - t) + sum
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sum = t
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result = sum + c
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func sumPairwise[T](x: openArray[T], i0, n: int): T =
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if n < 128:
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result = x[i0]
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for i in i0 + 1 ..< i0 + n:
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result += x[i]
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else:
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let n2 = n div 2
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result = sumPairwise(x, i0, n2) + sumPairwise(x, i0 + n2, n - n2)
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func sumPairs*[T](x: openArray[T]): T =
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## Pairwise (cascade) summation of `x[i0:i0+n-1]`, with O(log n) error growth
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## (vs O(n) for a simple loop) with negligible performance cost if
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## the base case is large enough.
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##
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## See, e.g.:
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## * https://en.wikipedia.org/wiki/Pairwise_summation
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## * Higham, Nicholas J. (1993), "The accuracy of floating point
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## summation", SIAM Journal on Scientific Computing 14 (4): 783–799.
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##
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## In fact, the root-mean-square error growth, assuming random roundoff
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## errors, is only O(sqrt(log n)), which is nearly indistinguishable from O(1)
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## in practice. See:
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## * Manfred Tasche and Hansmartin Zeuner, Handbook of
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## Analytic-Computational Methods in Applied Mathematics (2000).
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let n = len(x)
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if n == 0: T(0) else: sumPairwise(x, 0, n)
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