# Name

recons3d_4nn_ctf - calculate CTF-corrected 3-D reconstruction from a set of projections using three Eulerian angles, two shifts, and CTF settings for each projeciton image

# Usage

# calculate reconstruction using odd-numbered projections

- stack = "my_data.hdf"
- numproj = EMUtil.get_image_count(stack)
- list_proj = range(0,numproj,2):
- vol = recons3d_4nn_ctf(stack, list_proj, snr, sign [, symmetry])

## Input

- stack
name of the stack file containing projection data, projections have to be squares, i.e.,

**nx=ny**- list_proj
- list of projections to be included in the reconstruction
- snr
- Signal-to-Noise Ratio of the data (default = 1.0)
- sign
- sign of the CTF (for convenience for cry data the sign of the CTF is usually inverted and set to +1 so the particles appear to be bright on the dark background) (default = 1)
- symmetry
- point-group symmetry to be enforced, each projection will enter the reconstruction in all symmetry-related directions. The possibilities are

## Output

- vol
- the 3-D reconstructed volume

# Description

The command requires all parameters to be stored in headers of projection images as:

- proj.set_attr_dict({'phi':phi, 'theta':theta, 'psi':psi, 's2x':sx, 's2y':sy})
- proj.set_attr_dict({'ctf_applied':0})
CTF parameters need to be stored as an EMAN CTF object (see CTF_info for more information)

If projection images were already multiplied by the CTF, set attribute ctf_applied to 1.

# Method

# Reference

# Author / Maintainer

Pawel A. Penczek

# Keywords

- category 1
- INVERSION
- category 2
- FOURIER

# Files

reconstruction.py

# See also

# Bugs

None. It is perfect.