xmipp_classify_analyze_cluster (v3.0)


Score the images in a cluster according to their PCA projection It is assumed that the cluster is aligned as is the case of the output of CL2D or ML2D


-i <metadatafile>
metadata file with images assigned to the cluster
-o <metadatafile>
output metadata
--ref <img=>
if an image is provided, differences are computed with respect to it
--basis <stackName>
write the average (image 1), standard deviation (image 2) and basis of the PCA in a stack
--NPCA <dim=2>
PCA dimension
--iter <N=10>
Number of iterations
--maxDist <d=3>
Maximum distance Set to -1 if you don't want to filter images
Don't use a circular mask

Examples and notes

xmipp_classify_analyze_cluster -i images.sel --ref referenceImage.xmp -o sortedImages.xmd --basis basis.stk

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