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</source>
== Select residues for Execute a clustering analysis ==
All spins of one cluster ID will be optimised as one model. <br>
Several cluster ID will result in all those spins being optimised separately, but again with all spins together. <br>
Have a look at the '''model_loop()''' method of the '''specific_analyses.relax_disp.api''' module, <br>
and the function '''specific_analyses.relax_disp.disp_data.loop_cluster''' which it uses.
=== Create data pipe for cluster analysis ===
The commands be performed in the GUI
# '''pipe.copy''' -> User functions (n-z) -> pipe -> copy
# '''pipe.switch''' -> User functions (n-z) -> pipe -> switch
# '''pipe.switch''' -> User functions (n-z) -> relax_disp -> select_model
# '''minimise''' -> User functions (a-m) -> minimise
# and so forth...
<source lang="python">
set_id="cluster NS 2-site expanded"
pipe.copy(pipe_from='NS 2-site expanded', pipe_to=set_id, bundle_to='relax_disp')
pipe.switch(pipe_name='cluster NS 2-site expanded')
relax_disp.select_model(model='NS 2-site expanded')
</source>
=== Select residues for clustering ===
Let us select residue based on a criterion that is the same model which are fit.
</source>
== Execute a clustering analysis ==The commands be performed in Run the GUI# '''pipe.copy''' -> User functions (n-z) -> pipe -> copy# '''pipe.switch''' -> User functions (n-z) -> pipe -> switch# '''pipe.switch''' -> User functions (n-z) -> relax_disp -> select_model# '''minimise''' -> User functions (a-m) -> minimise# and so forth... <source lang="python">set_id="cluster NS 2-site expanded" pipe.copy(pipe_from='NS 2-site expanded', pipe_to=set_id, bundle_to='relax_disp')pipe.switch(pipe_name='cluster NS 2-site expanded')relax_disp.select_model(model='NS 2-site expanded')</source> and then run it.<source langanalysis ="python">script(file='cluster.py', dir=None)</source>
= See also =
[[Category:Tutorials]]