# Computing average of time deltas

**URL:** <https://www.ruby-forum.com/t/computing-average-of-time-deltas/89306>\
**Category:** Ruby\
**Created:** [March 19, 2007, 12:59pm UTC](https://www.ruby-forum.com/t/computing-average-of-time-deltas/89306 "2007-03-19T12:59:38Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![splattael](https://www.ruby-forum.com/letter_avatar_proxy/v4/letter/s/858c86/32.png) [@splattael](https://www.ruby-forum.com/u/splattael)\
**Post date:** [March 19, 2007, 12:59pm UTC](https://www.ruby-forum.com/t/computing-average-of-time-deltas/89306/1 "2007-03-19T12:59:38Z")

</div>

Hello,

Just to make sure I am not reinventing the wheel™ again: is there a  
function/lib in Ruby which computes average of timespans? e.g.

first task took 1s:100ms  
second task took 1s:400ms  
third task took 3s:500ms  
--------  
average 2s:000ms

TIA,  
Peter  
\_\_  
[http://www.rubyrailways.com](http://www.rubyrailways.com) :: Ruby and Web2.0 blog  
[http://scrubyt.org](http://scrubyt.org) :: Ruby web scraping framework  
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---

<div class="post-metadata">

**Author:** ![splattael](https://www.ruby-forum.com/letter_avatar_proxy/v4/letter/s/858c86/32.png) [@splattael](https://www.ruby-forum.com/u/splattael)\
**Post date:** [March 19, 2007, 2:56pm UTC](https://www.ruby-forum.com/t/computing-average-of-time-deltas/89306/2 "2007-03-19T14:56:11Z")

</div>

On Mar 19, 5:58 am, Peter S. [removed\_email\_address@domain.invalid](mailto:removed_email_address@domain.invalid) wrote:

> Just to make sure I am not reinventing the wheel™ again: is there a  
> function/lib in Ruby which computes average of timespans? e.g.
> 
> first task took 1s:100ms  
> second task took 1s:400ms  
> third task took 3s:500ms  
> --------  
> average 2s:000ms

The Benchmark class lists an example of doing this for a fixed set of  
discrete known tasks:

```
     require 'benchmark'

     n = 50000
     Benchmark.benchmark(" "*7 + CAPTION, 7, FMTSTR, ">total:",

```

“\>avg:”) do |x|  
tf = x.report(“for:”) { for i in 1…n; a = “1”; end }  
tt = x.report(“times:”) { n.times do ; a = “1”; end }  
tu = x.report(“upto:”) { 1.upto(n) do ; a = “1”; end }  
[tf+tt+tu, (tf+tt+tu)/3]  
end

```
 The result:

                   user system total real
      for: 1.016667 0.016667 1.033333 ( 0.485749)
      times: 1.450000 0.016667 1.466667 ( 0.681367)
      upto: 1.533333 0.000000 1.533333 ( 0.722166)
      >total: 4.000000 0.033333 4.033333 ( 1.889282)
      >avg: 1.333333 0.011111 1.344444 ( 0.629761)

```

It would also be pretty easy to modify the Benchmark.bmbm method to do  
this. Just sum and average the results calculated on line 277:  
res = Benchmark::measure(&item)

A side note: if you have a never-ending sequence of ‘tasks’ (such as a  
task repeated every update frame in a renderer) it is easier to  
calculate - and sometimes more desirable - to use a low-pass filter  
rather than a running average on a circular- or windowed-list.

For example:  
avg\_task\_time += ( current\_task\_time - avg\_task\_time ) / inertia

The higher the ‘inertia’, the less the formula will react to  
measurement spikes and the longer it will take to reach a new average.  
The closer ‘inertia’ is to zero, the quicker it will react to changes.