Zhong's name rule, function end with verbs
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|## page was renamed from get defocus|
get_defocus - Estimate defocus from 1D rotationally averaged power spectrum. This function is semi-automated, and requires the user to give correct cut_off frequency to determine the area of power spectrum for defocus estimation.
defocus = get_defocus((fnam_roo, volt=300,ps=1,cs=2,amplitude_contrast=.1,f_start=30,f_stop=8,docf="a",skip="#",round_off=100,nr1=3,nr2=6)
- document file name of 1D rotational average of power spectrum
- pixel size of the micrograph
- Sherical abberation constant
- amplitude constrast ratio
- low frequency limit (in Ansgtrom) of selecting power spectrum containing strong CTF for defocus estimation. The default value is 30 Angstrom.
- high frequency limit (in Angstrom) of selecting power spectrum containing strong CTF for defocus estimation. The default value is 8 Angstrom.
- 1D power spectrum document file format, either standard spider one "s" or arbitrary format "a"
- the mark of comments in the document file, such as ";", or "#"
- round_off error,by default it is set as 100 Angstrom. By adjusting this number( set as 0.1), the estimated defocus can be accurate to 0.01 Angstrom.
- the highest rank of polynomials used to fit envelop function
- the highest rank of polynomials used to fit background noise
- the estimated defocus in Angstrom.
- The function requires the user to define the area in the 1D rotationally averaged power spectrum for defocus estimation.
- Empirically power spectrum from 1/30 Ansgtrom to 1/8 Angstrom contains discernable CTF traces, and tends to give estimation which is close to the true defocus setting.
- The starting frequency is supposed to exclude the protein peak, and other spurious peaks caused by artifacts.
- The stopping freqeuncy is supposed to exclude too flat area of the power spectrum in high frequency area, which tends to underestimate the defocus.
- This function won't estimate astigmatsim.
- Constrained simplex method.
.1. 1. Barrodale and F.D.K. Roberts L1 solution to linear equations subject to linear equality and inequality constraints ACM TOMS 6 (1980), 231-235.
.2. Z. Huang, P. R. Baldwin, S.Mullapudi, and P .A. Penczek, Automated determination of parameters describing power spectra of micrograph images in electron microscopy. J. Struct. Biol. 144 (2003), pp. 79–94.
Author / Maintainer
- category 1
["guess defocus"],["pw extract"]
- works for most people, has been tested; test cases/examples available.
None. It is perfect.