Classification of 2D images

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Classify 2D images to increase the SN ratio.

To classify 2D images, use the mrcImageClusterAnalysis command. This cluster analysis calculates distance directly based on rotation and correlation, so it is a greatly time-consuming command. When calculation has finished, a dendrogram (tree diagram) can be created using a program named clusterShow to display the classification results of the image.

Then, extract clusters from the dendrogram to average them.

With regard to this matter, programs such as spider are nice because they have enriched GUI. On Eos, new programs are currently developed.

Exercise: Try clustering using simulated data.

First, move to the directory below:

$ cd 2DClustering/test 

Then, create a model.

$ ./modelCreate 

After that, execute make like below:

$ make 

The steps executed thereafter are displayed one by one as shown in the figure below:

How to use this Makefile-------------------
make Init 
make Pad
make Log

If make Log stopped in mid-flow, you can recalculate cluster in the middle by make ReLog

make LogPS

Refinement Start You must create xxxx.clstlst and xxxx.clstref, judging from ClusterTree:logps/padsortmon/avgsortmon.


If you want to repeat refinement,


Refinement End Execute make actually.