Classification of 2D images
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.
After that, execute make like below:
The steps executed thereafter are displayed one by one as shown in the figure below:
How to use this Makefile-------------------
make Init make ALLROIS make Pad make Log
If make Log stopped in mid-flow, you can recalculate cluster in the middle by make ReLog
Refinement Start You must create xxxx.clstlst and xxxx.clstref, judging from ClusterTree:logps/padsortmon/avgsortmon.
xxxx.clstlst xxxx.fitlst xxxx.clstavg
If you want to repeat refinement,
Refinement End Execute make actually.