Re: [cctbxbb] model selection

16 Aug 2018

Hi Pavel,
...
Speaking of consistency, 'selection' of 'atom_selection_cache' uses
'string' as the argument, not selstr as in 'model', example:
Indeed this is not very consistent. I don't remember if it was in original
model, or I did it. Anyway, I'll change selstr to string for consistency.
...
I see the different between these flavors of select*. Ok, I afraid I'll
have to read the code each time I use these..
Forgetting to use atom_selection_cache() function at all should help with
this.

Oleg.
...
Pavel
On 8/16/18 16:01, Oleg Sobolev wrote:
Hi Pavel,
Currently model class has three selection methods:
...
def selection(self, selstr, optional=True):
Takes selection string, returns bool selection
def select(self, selection):
...
Takes selection (bool or iselection), applies it to self and returns
selected part of model object.
def iselection(self, selstr):
...
Same as first, but returns iselection.
which is hideously confusing with zero chance to remember, and also
...
inconsistent with the rest.
Let me disagree on the point of inconsistency with the rest.
selection and iselection functions are available with exactly same meaning
for atom_selection_cache.
select is available with exact same meaning (returning part of an object)
in hierarchy, af_shared_atom, flex.vec3_double, xray_structure etc which
you pointed out.
...
Can we consolidate all three into one ".select()" that would allow taking
bool or int or str?
No, because they are doing different things. Selection and iselection
wraps atom_selection_cache functionality and not duplicating those of
select() function. ".select()" function already has the described
functionality.
...
Or you think there are philosophical arguments against it?
Yes, and practical ones as well. I'm caching atom_selection_cache inside
model object, so you don't have to construct it again if you use wrappers
available in model class. hierarchy.atom_selection_cache() is not a free
function to the point I had to pass the cache around to avoid constructing
it again to achieve measurable speedup. Especially for larger models.
At the very least, please use model.get_atom_selection_cache() instead of
constructing it.
Best regards,
Oleg Sobolev.
...
Pavel
On 8/16/18 15:00, CCTBX commit wrote:
Repository : ssh://g18-sc-serv-04.diamond.ac.uk/cctbx
On branch  : master
------------------------------
commit c98b44997e8eb7bf53ee828f510b933cd5167758
Author: Oleg Sobolev  
Date:   Thu Aug 16 15:00:20 2018 -0700
Proper use of model class
------------------------------
c98b44997e8eb7bf53ee828f510b933cd5167758
mmtbx/model/model.py | 3 +--
1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/mmtbx/model/model.py b/mmtbx/model/model.py
index 6f2247452..87412f95c 100644
--- a/mmtbx/model/model.py
+++ b/mmtbx/model/model.py
@@ -2312,8 +2312,7 @@ class manager(object):
     sizes = flex.int()
     h = self.get_hierarchy()
     if(macro_molecule_only):
-      asc = h.atom_selection_cache()
-      s = asc.selection("protein or nucleotide")
+      s = self.selection("protein or nucleotide")
       h = h.select(s)
     for r in h.residue_groups():
       sizes.append(r.atoms().size())
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