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You may also wish to look at [[/EMAN2/programs/e2refine2d]] You may also wish to look at: [[EMAN2/Programs/e2refine2d|e2refine2d]]
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 * input_fp
 * input_fp_basis
 * input_fp_basis_proj
 * classmx_00
 * classes_init
 * allrefs_XX
 * basis_XX
 * aliref_XX
 * simmx_XX
 * input_XX_proj
 * classmx_XX
 * classes_XX
 * '''input_fp''' - rotational/translational invariants for each particle
 * '''input_fp_basis''' - MSA basis vectors (images) from input_fp
 * '''input_fp_basis_proj''' - MSA subspace projections of the input_fp invariants
 * '''classmx_00''' - Initial classification of particles, same format as [[EMAN2/ClassmxFiles|classmx]] above
 * '''classes_init''' - Initial set of class-averages from invariant method (not very good usually)
 * '''allrefs_XX''' - All of the references (sorted) to be used for the current iteration
 * '''basis_XX''' - MSA basis from allrefs_xx
 * '''aliref_XX''' - Subset of allrefs used for alignment of raw particles
 * '''simmx_XX''' - Similarity matrix in same format as [[EMAN2/SimmxFiles|simmx]] above
 * '''input_XX_proj''' - Aligned particles projected into '''basis_XX''' subspace
 * '''classmx_XX''' - Classification matrix for the current iteration (as above)
 * '''classes_XX''' - Class averages at the end of the iteration. The highest numbered classes_XX file is the final output of the program

EMAN2 Concepts and Conventions

Modular functions in EMAN2

Many aspects of EMAN2 are modular, meaning new functions can be easily added for a variety of tasks. These categories are used in the GUI and from the command-line, and are not just useful for programmers. For example, the '--process' option in e2proc2d.py and e2proc3d.py uses 'processors' as defined below.

  • Processors - Filters, masks and other basic image processing operations

  • Comparators (cmp) - Similarity metrics (cmp) for comparing two images/volumes

  • Aligners - Algorithms for aligning one image/volume to another

  • Averagers - Methods for averaging many images/volumes together

  • Projectors - Generate 2-D projections of 3-D volumes (or 1-D projections of 2-D images)

  • Reconstructors - Generate 3-D volumetric reconstructions from sets of 2-D images and orientation paramters

  • Analyzers - Perform various analyses on sets of images/volumes

  • Symmetries - Permissible symmetries to use in EMAN2

  • Orientation Generators (orientgen) - Methods for generating sets of orientations filling an asymmetric unit

Information on specific files used in 3-D single particle refinement

This section documents the contents of all of the files produced by running e2refine.py in one of the refine_xx directories.

Information on specific files used in 2-D reference-free class-averaging

You may also wish to look at: e2refine2d

  • input_fp - rotational/translational invariants for each particle

  • input_fp_basis - MSA basis vectors (images) from input_fp

  • input_fp_basis_proj - MSA subspace projections of the input_fp invariants

  • classmx_00 - Initial classification of particles, same format as classmx above

  • classes_init - Initial set of class-averages from invariant method (not very good usually)

  • allrefs_XX - All of the references (sorted) to be used for the current iteration

  • basis_XX - MSA basis from allrefs_xx

  • aliref_XX - Subset of allrefs used for alignment of raw particles

  • simmx_XX - Similarity matrix in same format as simmx above

  • input_XX_proj - Aligned particles projected into basis_XX subspace

  • classmx_XX - Classification matrix for the current iteration (as above)

  • classes_XX - Class averages at the end of the iteration. The highest numbered classes_XX file is the final output of the program

single_image_iso_c.png

EMAN2/Concepts (last edited 2018-10-08 13:00:17 by SteveLudtke)