Name

avgvar_CTF- Calculates average and variance for an image series with CTF correction.

Usage

Calculate average and variance of image stack with CTF correction, and without applying current alignment parameters:

• avgvar_CTF(data, mode='b')

Calculate average and variance of image stack with CTF correction using current alignment parameters:

• avgvar_CTF(data, mode='a')

Calculate average and variance of only the even numbered images with CTF correction and without using current alignment parameters:

• avgvar_CTF(data, mode='b', use_odd = False)

Calculate average and variance of only the odd numbered images between images 3 and 57, inclusive, without CTF correction and using current alignment parameters:

• avgvar_CTF(data, mode='a', i1 = 3, i2 = 57, use_even=False)

Input

data

image stack, must be 2D, and must be in real space. CTF information must be provided in file headers (for details see I_O).

mode

whether to apply alignment parameters. Default mode='a' means apply parameters

ali_params

name of the attribute alignment parameters are stored under in image headers

rot_method

specifies the function by which images are rotated/shifted if alignment parameters are to be applied. This is only relevant for the case where images are 2D, in which case rot_method can be either rot_shift2D or rotshift2dg, with the default being rot_shift2D. If images are 3D, rot_shift3D will be used to rotate/shift the images.

interp

interpolation method to use for rot_method when applying alignment parameters.

i1

index of first image to be used.

i2

index of last image to be used. If i2 = 0, then i2 defaults to one less than number of images in the data

use_odd

images with indices between i1 and i2 which are odd are used if and only if use_odd is set to True. Default is True.

use_even

images with indices between i1 and i2 which are even are used if and only if use_even is set to True. Default is True.

snr

signal to noise ratio, default 1.0

Output

tavg

Inverse fourier transform of the best estimate (Wiener filter) of all the images used in the calculation (as determined by i1, i2, use_even and use_odd).

var

Variance, in real space

Description

The variance is calculated as: `1/(n-1)]*[sum_j (O_j - F^{-1}(H_j*O))^2 `, where the sum's index ranges over all images used in the calculations, n is the number of images used in the calculations, O_j is the j-th image in real space, O is the Weiner filter of images used in the calculation, F^{-1} denotes inverse fourier transform operator, and H_j is the CTF of the j-th image

Author / Maintainer

Jia Fang

Keywords

category 1

UTILITIES

Files

statistics.py

See also

mad_scalar, mul_scalar, add_img2, sub_img, mul_img

Maturity

• Works for author

Bugs