10.3.1. Atom selection Hierarchy — MDAnalysis.core.selection¶
This module contains objects that represent selections. They are constructed and then applied to the group.
In general, Parser.parse() creates a Selection object
from a selection string. This Selection object is then passed
an AtomGroup through its
apply() method to apply the
Selection to the AtomGroup.
This is all invisible to the user through the
select_atoms() method of an
AtomGroup.
-
class
MDAnalysis.core.selection.AltlocSelection(parser, tokens)[source]¶ Select atoms based on ‘altLoc’ attribute
-
class
MDAnalysis.core.selection.AtomICodeSelection(parser, tokens)[source]¶ Select atoms based on icode attribute
-
class
MDAnalysis.core.selection.AtomNameSelection(parser, tokens)[source]¶ Select atoms based on ‘names’ attribute
-
class
MDAnalysis.core.selection.AtomTypeSelection(parser, tokens)[source]¶ Select atoms based on ‘types’ attribute
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class
MDAnalysis.core.selection.BackboneSelection(parser, tokens)[source]¶ A BackboneSelection contains all atoms with name ‘N’, ‘CA’, ‘C’, ‘O’.
This excludes OT* on C-termini (which are included by, eg VMD’s backbone selection).
-
class
MDAnalysis.core.selection.BaseSelection(parser, tokens)[source]¶ Selection of atoms in nucleobases.
Recognized atom names (from CHARMM):
‘N9’, ‘N7’, ‘C8’, ‘C5’, ‘C4’, ‘N3’, ‘C2’, ‘N1’, ‘C6’, ‘O6’,’N2’,’N6’, ‘O2’,’N4’,’O4’,’C5M’
-
class
MDAnalysis.core.selection.DistanceSelection[source]¶ Base class for distance search based selections
-
validate_dimensions(dimensions)[source]¶ Check if the system is periodic in all three-dimensions.
- Parameters
dimensions (numpy.ndarray) – 6-item array denoting system size and angles
- Returns
Returns argument dimensions if system is periodic in all three-dimensions, otherwise returns None
- Return type
-
-
class
MDAnalysis.core.selection.MoleculeTypeSelection(parser, tokens)[source]¶ Select atoms based on ‘moltypes’ attribute
-
class
MDAnalysis.core.selection.NucleicBackboneSelection(parser, tokens)[source]¶ Contains all atoms with name “P”, “C5’”, C3’”, “O3’”, “O5’”.
These atoms are only recognized if they are in a residue matched by the
NucleicSelection.
-
class
MDAnalysis.core.selection.NucleicSelection(parser, tokens)[source]¶ All atoms in nucleic acid residues with recognized residue names.
Recognized residue names:
- from the CHARMM force field ::
awk ‘/RESI/ {printf “’”’”%s”’”’,”,$2 }’ top_all27_prot_na.rtf
recognized: ‘ADE’, ‘URA’, ‘CYT’, ‘GUA’, ‘THY’
recognized (CHARMM in Gromacs): ‘DA’, ‘DU’, ‘DC’, ‘DG’, ‘DT’
Changed in version 0.8: additional Gromacs selections
-
class
MDAnalysis.core.selection.NucleicSugarSelection(parser, tokens)[source]¶ Contains all atoms with name C1’, C2’, C3’, C4’, O2’, O4’, O3’.
-
class
MDAnalysis.core.selection.PropertySelection(parser, tokens)[source]¶ Some of the possible properties: x, y, z, radius, mass,
Possible splitting around operator:
prop x < 5 prop x< 5 prop x <5 prop x<5
-
class
MDAnalysis.core.selection.ProteinSelection(parser, tokens)[source]¶ Consists of all residues with recognized residue names.
Recognized residue names in
ProteinSelection.prot_res.- from the CHARMM force field::
awk ‘/RESI/ {printf “’”’”%s”’”’,”,$2 }’ top_all27_prot_lipid.rtf
manually added special CHARMM, OPLS/AA and Amber residue names.
-
class
MDAnalysis.core.selection.RecordTypeSelection(parser, tokens)[source]¶ Select atoms based on ‘record_type’ attribute
-
class
MDAnalysis.core.selection.ResidSelection(parser, tokens)[source]¶ Select atoms based on numerical fields
Allows the use of ‘:’ and ‘-‘ to specify a range of values For example
resid 1:10
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class
MDAnalysis.core.selection.ResidueNameSelection(parser, tokens)[source]¶ Select atoms based on ‘resnames’ attribute
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class
MDAnalysis.core.selection.SegmentNameSelection(parser, tokens)[source]¶ Select atoms based on ‘segids’ attribute
-
class
MDAnalysis.core.selection.SelectionParser[source]¶ A small parser for selection expressions. Demonstration of recursive descent parsing using Precedence climbing (see http://www.engr.mun.ca/~theo/Misc/exp_parsing.htm). Transforms expressions into nested Selection tree.
For reference, the grammar that we parse is
E(xpression)--> Exp(0) Exp(p) --> P {B Exp(q)} P --> U Exp(q) | "(" E ")" | v B(inary) --> "and" | "or" U(nary) --> "not" T(erms) --> segid [value] | resname [value] | resid [value] | name [value] | type [value]
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parse(selectstr, selgroups, periodic=None)[source]¶ Create a Selection object from a string.
- Parameters
- Returns
The appropriate Selection object. Use the .apply method on
this to perform the selection.
- Raises
SelectionError – If anything goes wrong in creating the Selection object.
-
-
class
MDAnalysis.core.selection.StringSelection(parser, tokens)[source]¶ Selections based on text attributes
Supports the use of wildcards at the end of strings
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MDAnalysis.core.selection.grab_not_keywords(tokens)[source]¶ Pop tokens from the left until you hit a keyword
- Parameters
tokens (collections.deque) – deque of strings, some tokens some not
- Returns
values – All non keywords found until a keyword was hit
- Return type
list of strings
Note
This function pops the values from the deque
Examples
grab_not_keywords([‘H’, ‘and’,’resname’, ‘MET’]) >>> [‘H’]
grab_not_keywords([‘H’, ‘Ca’, ‘N’, ‘and’,’resname’, ‘MET’]) >>> [‘H’, ‘Ca’ ,’N’]
grab_not_keywords([‘and’,’resname’, ‘MET’]) >>> []