xmipp_mpi_angular_class_average (v3.0)


Make class average images and corresponding selfiles from angular_projection_matching docfiles.

See also
angular_project_library angular_projection_matching


-i <doc_file>
Docfile with assigned angles for all experimental particles
--lib <doc_file>
Docfile with angles used to generate the projection matching library
-o <root_name>
Output rootname for class averages and selfiles
Also output averages of random halves of the data
--wien <img=>
Apply this Wiener filter to the averages
--pad <factor=1.>
Padding factor for Wiener correction
--save_images_assigned_to_classes, --siatc
Save images assigned te each class in output metadatas

IMAGE SELECTION BASED ON INPUT DOCFILE (select one between: limit 0, F and R

--select <col=maxCC>
Column to use for image selection (limit0, limitF or limitR)
--limit0 <l0>
Discard images below
--limitF <lF>
Discard images above
--limitRclass <lRc>
if (lRc>0 && lRc< 100): discard lowest % in each class if (lRc<0 && lR>-100): discard highest % in each class
--limitRper <lRp>
if (lRp>0 && lRp< 100): discard lowest % if (lRp<0 && lRp>-100): discard highest %


--iter <nr_iter=0>
Number of iterations for re-alignment
--Ri <ri=1>
Inner radius to limit rotational search
--Ro <r0=-1>
Outer radius to limit rotational search ro = -1 -> dim/2-1
--mpi_job_size <size=10>
Number of images sent to a cpu in a single job 10 may be a good value

Examples and notes

Sample at default values and calculating output averages of random halves of the data
xmipp_angular_class_average -i proj_match.doc --lib ref_angles.doc -o out_dir --split

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