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 |