11.4.1. 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.AromaticSelection(parser, tokens)[source]
Select aromatic atoms.
Aromaticity is available in the aromaticities attribute and is made available through RDKit
- 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).
Changed in version 1.0.1: bb_atoms changed to set (from numpy array) performance improved by ~100x on larger systems
- 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’
Changed in version 1.0.1: base_atoms changed to set (from numpy array) performance improved by ~100x on larger systems
- class MDAnalysis.core.selection.ByResSelection(parser, tokens)[source]
Selects all atoms that are in the same segment and residue as selection
Changed in version 1.0.0: Use
"resindices"
instead of"resids"
(see #2669 and #2672)
- MDAnalysis.core.selection.FLOAT_PATTERN = '-?\\d*\\.?\\d*(?:e[-+]?\\d+)?'
Regular expression for recognizing a floating point number in a selection. Numbers such as 1.2, 1.2e-01, -1.2 are all parsed as Python floats.
- class MDAnalysis.core.selection.FloatRangeSelection(parser, tokens)[source]
Range selection for float values
- MDAnalysis.core.selection.INT_PATTERN = '-?\\d+'
Regular expression for recognizing un/signed integers in a selection.
- 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
.Changed in version 1.0.1: bb_atoms changed to set (from numpy array) performance improved by ~100x on larger systems
- 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
Changed in version 1.0.1: nucl_res changed to set (from numpy array) performance improved by ~100x on larger systems
- class MDAnalysis.core.selection.NucleicSugarSelection(parser, tokens)[source]
Contains all atoms with name C1’, C2’, C3’, C4’, O2’, O4’, O3’.
Changed in version 1.0.1: sug_atoms changed to set (from numpy array) performance improved by ~100x on larger systems
- class MDAnalysis.core.selection.PropertySelection(parser, tokens)[source]
Some of the possible properties: x, y, z, radius, mass,
Changed in version 2.0.0: changed == operator to use np.isclose instead of np.equals. Added
atol
andrtol
keywords to controlnp.isclose
tolerance.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.
Changed in version 1.0.1: prot_res changed to set (from numpy array) performance improved by ~100x on larger systems
- MDAnalysis.core.selection.RANGE_PATTERN = '\\s*(?:[:-]| to )\\s*'
Regular expression for recognising a range separator. Delimiters include “:”, “-”, “to” and can have arbitrary whitespace.
- class MDAnalysis.core.selection.RangeSelection(parser, tokens)[source]
Range selection for int values
- class MDAnalysis.core.selection.ResidSelection(parser, tokens)[source]
Select atoms based on numerical fields
Allows the use of ‘:’, ‘-’ and ‘to’ to specify a range of values For example
resid 1:10
- class MDAnalysis.core.selection.SameSelection(parser, tokens)[source]
Selects all atoms that have the same subkeyword value as any atom in selection
Changed in version 1.0.0: Map
"residue"
to"resindices"
and"segment"
to"segindices"
(see #2669 and #2672)
- class MDAnalysis.core.selection.SelectionParser(*p, **k)[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]
- parse(selectstr, selgroups, periodic=None, atol=1e-08, rtol=1e-05, sorted=True, rdkit_kwargs=None)[source]
Create a Selection object from a string.
- Parameters
selectstr (str) – The string that describes the selection
selgroups (AtomGroups) – AtomGroups to be used in group selections
periodic (bool, optional) – for distance based selections, whether to consider periodic boundary conditions
atol (float, optional) – The absolute tolerance parameter for float comparisons. Passed to
numpy.isclose()
.rtol (float, optional) – The relative tolerance parameter for float comparisons. Passed to
numpy.isclose()
.sorted (bool, optional) – Whether to sorted the output AtomGroup.
rdkit_kwargs (dict, optional) – Arguments passed to the RDKitConverter when using selection based on SMARTS queries
- 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.
Changed in version 2.0.0: Added atol and rtol keywords to select float values. Added rdkit_kwargs to pass arguments to the RDKitConverter
- class MDAnalysis.core.selection.SingleCharSelection(parser, tokens)[source]
for when an attribute is just a single character, eg RSChirality
New in version 2.1.0.
- class MDAnalysis.core.selection.SmartsSelection(parser, tokens)[source]
Select atoms based on SMARTS queries.
Uses RDKit to run the query and converts the result to MDAnalysis. Supports chirality.
- MDAnalysis.core.selection.gen_selection_class(singular, attrname, dtype, per_object)[source]
Selection class factory for arbitrary TopologyAttrs.
Normally this should not be used except within the codebase or by developers; it is called by the metaclass
MDAnalysis.core.topologyattrs._TopologyAttrMeta
to auto-generate suitable selection classes by creating a token with the topology attribute (singular) name. The function uses the provideddtype
to choose which Selection class to subclass:BoolSelection
for booleansRangeSelection
for integersFloatRangeSelection
for floats_ProtoStringSelection
for strings
Other value types are not yet supported and will raise a ValueError. The classes are created in the
_selectors
module to avoid namespace clashes.- Parameters
- Returns
selection
- Return type
subclass of Selection
- Raises
ValueError – If
dtype
is not one of the supported types
Example
The function creates a class inside
_selectors
and returns it. Normally it should not need to be manually called, as it is created for each TopologyAttr:>>> gen_selection_class("resname", "resnames", object, "residue") <class 'MDAnalysis.core.selection._selectors.ResnameSelection'>
Simply generating this selector is sufficient for the keyword to be accessible by
select_atoms()
, as that is automatically handled by_Selectionmeta
.See also
MDAnalysis.core.topologyattrs._TopologyAttrMeta
,
- 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’]) >>> []
- MDAnalysis.core.selection.is_keyword(val)[source]
Is val a selection keyword?
- Returns False on any of the following strings:
keys in SELECTIONDICT (tokens from Selection objects)
keys in OPERATIONS (tokens from LogicOperations)
(Parentheses)
The value None (used as EOF in selection strings)