# Julia equivalent of Python's "fsum" for floating point summation

**URL:** <https://discourse.julialang.org/t/julia-equivalent-of-pythons-fsum-for-floating-point-summation/17785>\
**Category:** General Usage\
**Tags:** python\
**Created:** [November 20, 2018, 5:16pm UTC](https://discourse.julialang.org/t/julia-equivalent-of-pythons-fsum-for-floating-point-summation/17785 "2018-11-20T17:16:28Z")\
**Posts on this page:** 1\
**Showing post:** 20

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**Author:** ![y4lu](https://avatars.discourse-cdn.com/v4/letter/y/47e85d/32.png) [@y4lu](https://discourse.julialang.org/u/y4lu)\
**Post date:** [November 23, 2018, 7:58am UTC](https://discourse.julialang.org/t/julia-equivalent-of-pythons-fsum-for-floating-point-summation/17785/20 "2018-11-23T07:58:22Z")

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It’s a pretty neat trick too, and definitely a hard default to argue against. I was just noticing that each pass of the pairwise sum makes a partial Kahan sum on the remaining values 50% cheaper

Another approach

```julia
function finiteDif_sum(arr, d= 0.0)
  x = 0.0; y=0.0;
  y += d;
  for i in arr
    x = x + x-y + d + i; ## +y-x -d ?
    y = y + i + y + i - x - d; ## and + x - y - i + d ?
    end;
  [x,y - d]
  end;

```

Add- might’ve gotten the x-y around the wrong way

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