lisc.objects.base.Base

class lisc.objects.base.Base

A class for the base object for LISC collections and analyses.

Attributes:

termslist of list of str

Terms words.

labelslist of str

The labels for each term.

inclusionslist of str

Inclusion words for each term.

exclusionslist of list str

Exclusion words for each term.

has_termsbool

Indicator for if the object has terms.

n_termsint

How many terms are included in the object.

__init__()

Initialize Base object.

Methods

__init__()	Initialize Base object.
add_labels(labels[, directory, ...])	Add the given list of strings as labels for the terms.
add_terms(terms[, term_type, directory, ...])	Add terms to the object.
check_terms([term_type])	Print out the current list of terms.
copy()	Return a copy of the current object.
drop_term(label)	Drop specified term(s) from the object.
get_index(label)	Get the index for a specified search term.
get_term(label)	Get a search term from the object.
make_search_term(label)	Create the combined search term for a selected term.
set_joiners([search, inclusions, exclusions])	Set joiners to use, specified for each term type.
unload_labels([verbose])	Unload labels from the object.
unload_terms([term_type, reset, verbose])	Completely unload terms from the object.

Attributes

has_terms	Indicator for if the object has terms.
labels	The labels for each term.
n_terms	How many terms are included in the object.

add_labels(labels, directory=None, check_consistency=True)

Add the given list of strings as labels for the terms.

Parameters:

labelslist of str or str

Labels for each term to add to the object. If list, is assumed to be labels. If str, is assumed to be a file name to load from.

directorySCDB or str, optional

Folder or database object specifying the file location, if loading from file.

check_consistencybool, optional, default: True

Whether to check the object for consistency after adding labels.

add_terms(terms, term_type=None, directory=None, append=False, check_consistency=True)

Add terms to the object.

Parameters:

termslist or dict or str

Terms to add to the object. If list, assumed to be terms, which can be a list of str or a list of list of str. If dict, each key should reflect a term_type, and values the corresponding terms. If str, assumed to be a file name to load from.

term_type{‘terms’, ‘inclusions’, ‘exclusions’}

Which type of terms to are being added.

directorySCDB or str, optional

Folder or database object specifying the file location, if loading from file.

appendboolean, optional, default: False

Whether to append the new term(s) to any existing terms. If False, any prior terms are cleared prior to adding current term(s).

check_consistencybool, optional, default: True

Whether to check the object for consistency after adding terms.

Examples

Add search terms, from a list:

>>> base = Base()
>>> base.add_terms(['frontal lobe', 'temporal lobe', 'parietal lobe', 'occipital lobe'])

Add inclusion terms, from a list:

>>> base.add_terms([[], ['brain'], [], []], term_type='inclusions')

Add exclusion terms, from a list:

>>> base.add_terms([['prefrontal'], [], [], []], term_type='exclusions')

check_terms(term_type='terms')

Print out the current list of terms.

Examples

Check added terms:

>>> base = Base()
>>> base.add_terms(['frontal lobe', 'temporal lobe', 'parietal lobe', 'occipital lobe'])
>>> base.check_terms() 
List of terms used:

frontal lobe    : frontal lobe
temporal lobe   : temporal lobe
parietal lobe   : parietal lobe
occipital lobe  : occipital lobe

Attributes:

term_type{‘terms’, ‘inclusions’, ‘exclusions’}

Which type of terms to use.

copy()

Return a copy of the current object.

drop_term(label)

Drop specified term(s) from the object.

Parameters:

labelstr or int or list

The label of the term to drop. If str, is the label of the term. If int, is used as the index of the term. If list, drops each element of the list.

get_index(label)

Get the index for a specified search term.

Parameters:

labelstr

The label of the search term.

Returns:

indint

The index of the requested search term.

Raises:

IndexError

If the requested term label is not found.

get_term(label)

Get a search term from the object.

Parameters:

labelstr or int

The requested term. If str, is the label of the term. If int, is used as the index of the term.

Returns:

termTerm

The full search term definition.

property has_terms

Indicator for if the object has terms.

property labels

The labels for each term.

make_search_term(label)

Create the combined search term for a selected term.

Parameters:

labelstr or int

The requested term. If str, is the label of the term. If int, is used as the index of the term.

property n_terms

How many terms are included in the object.

set_joiners(search=None, inclusions=None, exclusions=None)

Set joiners to use, specified for each term type.

Parameters:

search, inclusions, exclusions{‘OR’, ‘AND’, ‘NOT’}

Joiner to use to combine terms, for search, inclusions, and exclusions terms.

unload_labels(verbose=True)

Unload labels from the object.

unload_terms(term_type='terms', reset=True, verbose=True)

Completely unload terms from the object.

Examples

Unload added terms:

>>> base = Base()
>>> base.add_terms(['frontal lobe', 'temporal lobe', 'parietal lobe', 'occipital lobe'])
>>> base.unload_terms()
Unloading terms.

Attributes:

term_type{‘terms’, ‘inclusions’, ‘exclusions’, ‘labels’, ‘all’}

Which type of terms to unload.

resetbool, optional, default: True

Whether to reset in/exclusions to empty lists.

verbosebool, optional

Whether to be verbose in printing out any changes.

Examples using lisc.objects.base.Base

Database and Terms Lists

Database and Terms Lists

Tutorial 00: LISC Overview

Tutorial 00: LISC Overview

Tutorial 01: Words Collection

Tutorial 01: Words Collection

Tutorial 03: 1D Counts

Tutorial 03: 1D Counts

Tutorial 06: Collect Across Time

Tutorial 06: Collect Across Time