[ml] Statistics / software question

gershon bialer gershon.bialer at gmail.com
Sat May 12 01:06:13 PDT 2012


I think you can use Kalman smoothing (see
http://en.wikipedia.org/wiki/Kalman_filter#Fixed-interval_smoothers).
This should give you an estimate of the value and standard deviation
for each point, which I think you should be able to use for confidence
intervals.

R has a function KalmanSmooth, which might work. You could try a
simple model with T=Z=1.

On Fri, May 11, 2012 at 10:37 PM, Christoph Maier
<cm.hardware.software.elsewhere at gmail.com> wrote:
> The NaI(Tl) or better yet, CsI(Tl) is the stuff hard to get by.
> We need to find a Jeriellsworthesque way to cook that in our own kitchen, or
> at tastebridge.
>
> Looks like it's time for my (nowadays) semi-annual dose of noisebridge
> reality distortion soon.
>
> Data: CSV, if you please.
>
> On Fri, May 11, 2012 at 10:30 PM, Jake <jake at spaz.org> wrote:
>>
>> well i've stashed graphical plots of the bins, but I do not have stored
>> raw data at this time because my java program what makes these graphics
>> doesn't save the serial data to a file.  oops.
>>
>> But i will correct that asap and start providing data.  in the meantime
>> you can look at these plots:
>> http://spaz.org/~jake/r/mccad/rad/thorium-zoomed.png
>> http://spaz.org/~jake/r/mccad/rad/thorium-unzoomed.png
>> http://spaz.org/~jake/r/mccad/rad/carnotite-zoomed.png
>> http://spaz.org/~jake/r/mccad/rad/carnotite-unzoomed.png
>>
>> and you will notice that there's absolutely no data there, it's all noise.
>> I have determined that this is because my scintillating crystal of NaI(Tl)
>> is "fried" meaning the person who sold it to me was an asshole, and the
>> amount of blue light coming out of the crystal has nothing to do with the
>> energy of the original gamma.  Random data.
>>
>> fortunately I have other crystals (including a BGO crystal) and I will
>> capture more data soon, which will hopefully look more like this:
>>
>> http://spaz.org/~jake/r/mccad/rad/MCA2.Cs137.jpeg
>>
>> there is other data, from an older version of this detector with a
>> different crystal (a nasty ruined crystal but maybe not quite fried)
>> which you can look at here:
>>
>> http://spaz.org/~jake/r/mccad/rad/data/
>>
>> -jake
>>
>>
>> On Fri, 11 May 2012, Christoph Maier wrote:
>>
>>> Link to the raw data, please.
>>>
>>> On Fri, May 11, 2012 at 8:55 PM, Wladyslaw Zbikowski
>>> <embeddedlinuxguy at gmail.com> wrote:
>>>      Hi, my friend Jake has a little project for which we might be
>>>      able to
>>>      use some statistics expertise.
>>>
>>>      We are taking analog readings from a device (a voltage pulse).
>>>      The
>>>      voltage pulse represents the energy of a single X-ray particle
>>>      (in
>>>      MeV). We know what the energy signature is supposed to look like
>>>      for
>>>      this particular radioactive material; i.e. there are peaks where
>>>      certain energies are highly represented, and valleys where other
>>>      energy levels are rare. So we would like to correlate our
>>>      measurement
>>>      with the expected signature.
>>>
>>>      The problems are:
>>>
>>>      1. A lot of noise. We have a signal:noise ratio around 1:1 or as
>>>      good
>>>      as 4:1, because of background radiation and attempts at
>>>      shielding.
>>>
>>>      2. We don't know exactly how the voltage we read maps to MeV.
>>>      I.e.
>>>      Voltage is a function of Energy, presumably linear, but we don't
>>>      know
>>>      exactly the scale (how many MeV per volt).
>>>
>>>      SO in short, we have a graph of our data, and we want to
>>>      force-fit it
>>>      to the graph we expect. My idea is to apply noise removal and
>>>      scaling,
>>>      getting the closest possible match. Any thoughts on this? R?
>>>      Python?
>>>      Possible topic for a meetup? We can post the graphs and the
>>>      software
>>>      if anyone is interested to see.
>>>
>>>      Thanks in advance!
>>>      _______________________________________________
>>>      ml mailing list
>>>      ml at lists.noisebridge.net
>>>      https://www.noisebridge.net/mailman/listinfo/ml
>>>
>>>
>>>
>>>
>
>
> _______________________________________________
> ml mailing list
> ml at lists.noisebridge.net
> https://www.noisebridge.net/mailman/listinfo/ml
>



-- 
---------------------
Gershon Bialer


More information about the ml mailing list