Closed mahnen closed 6 years ago
small summary from the pdf:
Results:
My opinion on it:
/fhgfs/groups/app/fact/simulated/DispRegressor_v1.pmml
Hey,
Can you give more details on the plots you showed? I do not really understand what the different colors mean. Can you maybe add a plot where you just show the comparison for the old disp
method and your random forrest?
Also a correlation plot between the two methods might be interesting.
1) correlation plot between the two methods
2) comparison for the old disp method and your random forrest
I made some more plots. In theory, Disp = Distance for gamma-rays. The following plots are Disp vs Distance for the two methods. It looks to me rather like the current parametrization of Disp is a random number...
The last comparison is the size over theta^2 distribution. It shows that we can particularly gain something at higher sizes
Really nice, but I have some comments on that:
I would propose to have a brainstorming telcon (or skype con) next week (11.4. - 15.4.) to discuss this. But I agree with you, this is one of the main remaining issue FACT-Tools has to handle and your application of the RF regression is quite impressive.
I have looked up the definition of Dist in Sebastian Commichaus old PhD thesis. He there writes:
The image parameters DIST and ALPHA are so-colled source-dependent image parameters...
The drawing in my mind goes as follows:
Also, the current implementation of the alpha (by Kai?) looks source dependent:
`
//TODO: this might throw an NPE for source[1]
double auxiliary_angle = Math.atan( (source[1] - dist.getCenterY() )/(source[0] - dist.getCenterX()) );
//auxiliary_angle = auxiliary_angle / Math.PI * 180;
alpha = (dist.getAngle() - auxiliary_angle);
`
and also our implementation of Dist is source dependent, as Kai writes:
/**
- Quite simply the distance between the CoG of the shower and the calculated source position.
- @author kaibrugge /
So after all it looks to me that Dist for Gamma-MC is the MC-truth for Disp.
Sebastian C. further continues about the sign of the Disp parameter (M1 - single telescope!):
Because of the head-tail ambiguity in the 2nd moment analysis, the Disp method provides two possible solutions for the location of the source along the mayor axis of the Hillas ellipse. A possibility to overcome the head-tail ambiguity is to make use of the asymmetry parameter M3LONG. ... The achieved ratio of correct head-tail assignment is in the order of 70%, which strongly depends on the considered energy range.
The MC-truth (DIST) is really, like you mentioned, cleaning dependent etc..., which unfortunately breaks the streams-flow... you have to process it first and then build the Disp-RF and then run again.
Telcon next week - no problem.
Moved to our python classifier tools and works quite nicely
Hi guys,
I wrote a little something about the current status of the Disp-parameter. In particular it would be quite important to get this Parameter estimated better.
disp_rf.pdf