EMAN2 Analyzer Manual


Last modified on Mon, 19 Jul 2010 13:03:27 CDT
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Analyzer Name Parameters Description
kmeans int calcsigmamean: Computes standard deviation of the mean image for each class-average (center), and returns them at the end of the list of centers
int maxiter: maximum number of iterations
int minchange: Terminate if fewer than minchange members move in an iteration
int mininclass: Minumum number of particles to keep a class as good (not enforced at termination
int ncls: number of desired classes
int slowseed: Instead of seeding all classes at once, it will gradually increase the number of classes by adding new seeds in groups with large standard deviations
int verbose: Display progress if set, more detail with larger numbers (9 max)
k-means classification
pca emdata mask: mask image
int nvec: number of desired principal components
Principal component analysis
pca_large emdata mask: mask image
int nvec: number of desired principal components
Principal component analysis
svd_gsl emdata mask: mask image
int nimg: total number of input images, required even with insert_image()
int nvec: number of desired basis vectors
Singular Value Decomposition from GSL. Comparable to pca
varimax emdata mask: mask image
varimax rotation of PCA results