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Author Topic: estimate parameter in protomo
himes.benj-
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Post estimate parameter in protomo
on: January 20, 2014, 21:02
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I am a bit confused about the "estimate" parameter in Area matching.

The area matching seems to proceed faster when estimate : true, which seems a bit counterintuitive to me. I would think that using stored values, rather than estimating on the fly would result in a faster calculation?

Additionally, if estimate is set to true for each cycle, is the geometry refinement really taken into account? Does this produce a less accurate tilt series alignment overall?

Could you please elaborate a little bit on how the geometric parameters are estimated, and how true/false settings may affect the potential outcome?

Thank you,

Ben

winkler
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Post Re: estimate parameter in protomo
on: January 21, 2014, 20:07
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Why is it counterintuitive? When you look at the plots of the in-plane rotations and correction factors you notice that they follow a trend, they are not random. So, if the "estimate" parameter is true, then the in-plane rotation and correction factors of the neighboring image are good starting values, especially so for the initial cycle where you set the in-plane rotation to zero, for example. What you probably observed is that the optimization algorithm converges faster when the initial values are closer to the ideal values. I would expect that behavior for the first few cycles. For later cycles, when the geometric parameters do not change substantially any more, it might be better to use the stored values from the previous cycle as a starting point for area matching.

The "estimate" parameter only affects the initial geometric values of a particular cycle. If it is true, the in-plane rotation and corrections are simply copied from the neighbor image that has just been aligned (in the same cycle). Thinking about it, a better way than just copying the values would be to extrapolate from the already measured corrections from all images at lower tilt that have already been matched.

The choice of the estimated initial values could have an influence on the outcome of the optimization if different local minima would exist and the algorithm gets caught in the wrong one. I haven't found any indications so far that this is happening, though. A slightly different problem that we observed, however, is double or multiple peaks in the correlation function, and the true peak is not necessarily the highest one. This is very obvious when displaying the peaks and is usually related to incorrect values for the back-projection body size.

robertcore-
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Post Re: estimate parameter in protomo
on: January 23, 2018, 05:37
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