sisl.geom.AtomSeq

class sisl.geom.AtomSeq

Bases: AtomIndex

Classify atoms based on their indices using a sequence string.

Parameters:

seq – sequence indicating the indices that you want to match (see examples)

Examples

>>> seq = AtomSeq("1-3")
>>> geom.sub(seq) == geom.sub([1,2,3])
>>> seq = AtomSeq("1-3,7")
>>> geom.sub(seq) == geom.sub([1,2,3,7])
>>> seq = AtomSeq("1-3,7:")
>>> geom.sub(seq) == geom.sub([1,2,3,*range(7, len(geom))])
>>> seq = AtomSeq("1-3,6,9:2:")
>>> geom.sub(seq) == geom.sub([1,2,3,6,*range(9, len(geom), 2)])

See also

strmap, lstranges

Methods

categorize(geometry, *args, **kwargs)	Do categorization
is_class(name[, case])	Query whether name is one of the keywords of this class
kw(**kwargs)	Create categories based on keywords
mask(*args, **kwargs)	Boolean array which is true for the objects in this category

Attributes

name	Name of category

classmethod is_class(name, case=True)

Query whether name is one of the keywords of this class

The keywords are the key and aliases class arguments. Sub-classes may override this method for other matching rules.

Parameters:

• name (str) – the keyword to match

• case (bool) – whether the match is case-sensitive

Return type:

bool

classmethod kw(**kwargs)

Create categories based on keywords

This will search through the inherited classes and return and & category object for all keywords.

Since this is a class method one should use this on the base category class in the given section of the code.

Each keyword matches a sub-class through is_class, first case-sensitive, then case-insensitive. The value is passed to the matched class:

• True creates it without arguments (odd=True),

• a dict is passed as keyword arguments (odd={}),

• anything else is passed as the single argument (Z="C").

Raises:

• TypeError – if no keywords are given

• ValueError – if a keyword matches no, or more than one, sub-class

categorize(geometry, *args, **kwargs)

Do categorization

Parameters:

geometry (Geometry)

mask(*args, **kwargs)

Boolean array which is true for the objects in this category

The arguments are the same as for categorize. The parts of a composite category share their calculations, e.g. the neighbor search of AtomNeighbors.

Returns:

1D boolean array, one value per categorized object.

Return type:

numpy.ndarray

property name

Name of category