Table column convention

col 1: tag

Identifies the particle number, so that each particle in the [data folder] indexed by the table is identified.

col 2: align

0 or 1 Used when a table is fed into Dynamoas initial table for an alignment project. Value 1 tells Dynamo that the particle is to be used during an alignment project, values 0 skips the particle. {T|hola}

col 13: ftype (type of fourier sampling)

Describes the fraction of the Fourier space covered by the particle. Basically it represents the imaging geometry. 0 or 'full' 1 or 'single' beam along z, tilt around y 2 or 'singlex' beam along z, tilt around x 3 or 'cone', beam along z 4 or 'double', 'dual' beam along z, tilts around y and x 5 or 'custom' 6 or 'tilt_z_beam_y' beam along y, tilt around z 7 or 'tilt_x_beam_y' beam along y, tilt around x

For total characterization of the Fourier components covered by the particle, the information in this column needs to be complemented with other columns [14 to 19] depending on the ftype.

ftype 5: custom

When a particle is indicated to have a custom mask, then the data folder needs to include a volume file with zeros and ones that describes this custom geometry. This is useful for instance when the user wants to explicite the different Fourier planes sampled during tilt colection, instead of describing them like a wedge. The file representing this fsampling should be called pfmask, i.e. pfmask_00010.em for the corresponding particle particle_00010.em and so on.

cols 24-26: position in tomogram

Given in pixels.

col 34: reference

This column is written by Dynamo during the computation of a multireference alignment project. It marks the reference channel that yielded the highest score for the particle. A "reference" can be seen as a "class" produced by multireference alignment and classification.

col 35: subreference

This column is typically written by Dynamo while creating averages of the particles assigned to different clusters computed through PCA+Kmeans or Hierarchical Ascending Clustering. Thus, in Dynamo jargon, "subreference" can be seen as a "class" produced by classification through PCA+ Kmeans or HAC. The name "subreference" comes from the fact that we frequently use PCA analysis on top of the results attained by Multireference Analysis.