Use the ClassClean logic to separate good particle images from bad “junk” particles, a general prerequisite for obtaining a good 3d structure.
The ClassClean logic computes a quality score for particles in context of a group of particles (“class”). Therefore, this logic requires particles to be aligned and classified beforehand - either by assignment to a reference from Alignment or a class from Classification. ClassClean can be operated in two modes: In “clean” mode particles are evaluated within each class and dependent on chosen parameters a certain fraction of only the best particles is kept. In “refine” mode existing classes from a previous “clean” mode run may be supplemented with a new set of particles. These new particles are then i) assigned to the best matching class, ii) evaluated within this class and iii) either kept when they improve the quality measure of this class or discarded. Using a circular mask helps in particle evaluation by removing background noise. Note: The ClassClean logic performs no alignment.
Use this mode to remove bad particle images from a data set.
Parameters | Description |
Class truncation - enabled | Use this option to define how many of the best particles should be kept per class at maximum |
→ Class truncation threshold | Maximum number of best particles to be kept for each class |
Class truncation - disabled | Use this option to define the fraction of best particles to be kept solely by the “Sigma value” |
Header key | Define whether classes should be defined by preceding alignment (“referenceData”) or classification (“ClusterMember”) |
Mask usage | Define whether no mask (“none”), a circular mask or a soft circular mask should be used. |
→ Relative radius | Define radius of the circular mask |
Minimum class size | Minimum number of particles to be kept within each class. |
Sigma value | Define in terms of standard deviations what fraction of the best particles should be kept. |
Input | Description |
Input Images | Particle images to be cleaned. Note: This particle images must have been aligned and/or classified |
Output | Description |
Class members | Good particle images to be kept |
Class sums | Class averages from cleaned classes containing only the good particles |
Discarded Images | Bad particles images discarded from the data |
New/Changed Header Values | Description |
ClassCleanClassQuality | Overall quality measure of the class the particle image belongs to |
ClassCleanImageQuality | Quality measure of the individual particle image within the context of its class |
classSize | Number of class members after cleaning |
Use this mode to add only good particle images to an already existing “cleaned” data set.
Parameters | Description |
Header key | Define whether classes should be defined by preceding alignment (“referenceData”) or classification (“ClusterMember”) |
Mask usage | Define whether no mask (“none”), a circular mask or a soft circular mask should be used. |
→ Relative radius | Define radius (in fractions) of the circular mask |
Input | Description |
Input data (Preclassified) | |
Input data (Unclassified) | |
Output | Description |
Class members | Good particle images to be kept |
Class sums | Class averages from cleaned classes containing only the good particles |
Discarded Images | Bad particles images discarded from the data |
New/Changed Header Values | Description |
ClassCleanClassQuality | Overall quality measure of the class the particle image belongs to |
ClassCleanImageQuality | Quality measure of the individual particle image within the context of its class |
classSize | Number of class members after cleaning |
referenceData/clusterMember(depending on user selection) | Class where the good “unclassified” images have been placed by ClassClean |