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- First use whole specified ROI, and fit for a solution
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- Eliminate statistically insignificant gamma lines; then use remaining gammas to decide peak ROI widths (and if should be further broken up?)
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To get rid of the degeneracy of rel-eff and rel-act:
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- Add an extra term to the Chi2 that forces the rel-act equation to be 1.0 at the lowest energy; maybe multiple difference of current rel-eff equation from 1.0 by the area of the largest peak in any of the ROIs
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Parameters to fit:
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- Energy offset; Energy gain adjust //will be fixed to begin with
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- Fwhm Parameters // Will be `num_parameters(FwhmForm)` number of these
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- RelEff coefs // There will be one more than the "order" of relative eff eqn
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- {Activity,Age} // One pair for each nuclide. Age will be mostly fixed, but can also be tied to another nuclide of the same elements age
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- Free float peaks {amplitude, width-multiple} // The width multiple is of what the Fwhm Parameters predict (e.g., 1.0 says use parameter value).
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Further things to consider:
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- Sum peaks - not totally sure how to handle - can there just be one parameter that controls strength of peak random summing, and then another for cascade?
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- For the relative efficiency chart, currently all markers for peaks info fall exactly on the
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RelEff line. What we should do is, after finding the solution, cluster the peaks together
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(similar to Act/Shield fit), and then make a template for each clustered peak (sum all peaks into
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a channel count array, with separate array for each clustered peak), with some threshold (like
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99% detection threshold) that if the clustered peaks area is less than, it just gets subtracted
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from the data, unless its the only peak for that ROI.
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Then fit the templates to data, and use the fit values to make the markers on the RelEff plot.
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I think the plotting JS can handle showing info for multiple nuclides in a single plots
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mouse-over. We will need to create new variable that is analogous to
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#RelActAutoSolution::m_fit_peaks, but maps multiple source nuclides to a single peak.
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- Sum peaks - not totally sure how to handle - can there just be one parameter that controls
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strength of peak random summing, and then another for cascade? For cascades we dont have
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gamma-x-ray coincidences (or is it the case we can just assume constant fraction between any
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gamma and any nuclide?), so we might need two parameters, one for gamams, one for gamma-neutrons
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