[AstroPy] JointFitter help

[Paul Kuin]

to quickly get a centroid, you can also use a simple weighted mean

I think it is like,

say z(x,y) is the value of the pixel,
posx = sum(x*z(x,y))/sum(x)
posy = sum(y*z(x,y))/sum(y)

On Wed, Feb 4, 2015 at 7:22 PM, Brandon Swift <bjswift at gmail.com> wrote:

> Sure thing, Nadia. In case you/someone else doesn't know, a regular
> digital camera has an alternating color filter pattern over the CMOS
> detectors like this http://en.wikipedia.org/wiki/Bayer_filter. I am
> trying to take a picture of a point-like source that has contrast to the
> surrounding background, and nail down the centroid of that as well (and as
> fast) as I reasonably can. I figure that using the raw pixel data instead
> of using the demosaiced and otherwise-processed JPEG that normally comes
> out the back end of the camera will help.
>
> So, yes, I'm trying to fit a 2D gaussian to R, G, and B channels
> simultaneously, each of which has their own checkerboard-like mask, like in
> the attached image/below.
>
>
> ​
> When doing the gaussian fit, the x/y_mean should be tied together between
> the 3 channels, and the x/y_stddev and theta should also be tied (to within
> chromatic effects of the lens), but the amplitude of each channel should be
> allowed to be different. Which all sounds very much like the example
> use-case described in the docstring of the JointFitter class!
>
> I had moderate success with fitting individual channels (convergence was
> sometimes flaky) and was about to try writing a custom 'Gaussian2Dx3' model
> class when I ran across JointFItter and thought it seemed like it would do
> nicely. Right now, I'm doing something like this, which isn't working right
> because I don't know how the inputs need to go but I've been trying to
> guess from the source code and errors generated:
>
>
> --------------------------------------------------------------------------------------------------------
> ## Define reasonable ranges for the fitting parameters (data centered at
> 0,0 pixel)
> gaussbounds = {'amplitude': [0.2, 0.8],  'x_mean':    [-2.0, 2.0],
>  'y_mean':    [-2.0, 2.0], 'x_stddev':  [0.2, 1.5], 'y_stddev':  [0.2, 1.5]}
>
> ## Create a model instance for each channel
> gaussR = models.Gaussian2D(0.5, 0.0, 0.0, 0.4, 0.4, bounds=gaussbounds)
> gaussG = models.Gaussian2D(0.5, 0.0, 0.0, 0.4, 0.4, bounds=gaussbounds)
> gaussB = models.Gaussian2D(0.5, 0.0, 0.0, 0.4, 0.4, bounds=gaussbounds)
>
> ## Trying to get these other inputs structured correctly to make
> JointFitter.__init__()
> ## complete smoothly.
> jointpars = {'gaussR':   [gaussR.x_mean, gaussR.y_mean, gaussR.x_stddev,
> gaussR.y_stddev, gaussR.theta],
>              'gaussG':   [gaussG.x_mean, gaussG.y_mean, gaussG.x_stddev,
> gaussG.y_stddev, gaussG.theta],
>              'gaussB':   [gaussB.x_mean, gaussB.y_mean, gaussB.x_stddev,
> gaussB.y_stddev, gaussB.theta] }
> initvals = [0.0, 0.0, 0.4, 0.4, 0.0]
>
> ## Here's what I'm feeding it, finally. I'm out of ideas!
> jointRGB = fitting.JointFitter({'gaussR':gaussR, 'gaussG':gaussG,
> 'gaussB':gaussB}, jointpars, initvals)
>
> --------------------------------------------------------------------------------------------------------
>
> Anyway, many thanks in advance for the help! Cheers,
> Brandon
>
>
>
> > Date: Wed, 4 Feb 2015 14:38:44 +0000
> > From: Nadezhda Dencheva <dencheva at stsci.edu>
> > Subject: Re: [AstroPy] JointFitter help
> >
> > Hi Brandon,
> >
> > Can you explain a bit more how you are doing the fitting?
> > It sounds like you are fitting a 2D Gaussian but I'm not sure what the
> data is?
> > What are the inputs to each model?
> >
> > Cheers,
> > Nadia
>
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>
>


-- 

* * * * * * * * http://www.mssl.ucl.ac.uk/~npmk/ * * * *
Dr. N.P.M. Kuin      (n.kuin at ucl.ac.uk)
phone +44-(0)1483 (prefix) -204927 (work)
mobile +44(0)7806985366  skype ID: npkuin
Mullard Space Science Laboratory  – University College London  –
Holmbury St Mary – Dorking – Surrey RH5 6NT–  U.K.
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