Character N-gram extraction¶
CharNgramsExtractor(n=2, lowercase=False, within_words=False, tokenizer=None)
A class for extracting character N-grams from a text - sequences of N characters taken with a sliding window over the string. Character N-grams are a standard feature of stylometry and authorship attribution (Stamatatos 2009) and can replace words in measures such as Burrows's Delta.
Whitespace runs are collapsed into a single space, punctuation marks are kept. With within_words=True N-grams do not cross word boundaries: the text is split into words by the tokenizer, punctuation is dropped, and words shorter than N yield no N-grams.
Raises:
ParameterError- annthat is not an integer of at least one, alowercaseorwithin_wordsthat is not abool.
The class extends the CharNgramsExtractor of the anyTS core with the hook of Russian: the words for within_words (the method tokenize(text)) are those of WordsExtractor, the tokens of the anySeg segmenter. Stress marks and soft hyphens are removed from the text before extraction. The list of N-grams is passed to delta as text units instead of words.
from ruts import CharNgramsExtractor
text = "Кот сидел на окне, а пёс - на полу."
ce = CharNgramsExtractor(n=3, lowercase=True)
ce.extract(text)[:6]
CharNgramsExtractor().extract(text)[:8]
CharNgramsExtractor(n=3, lowercase=True, within_words=True).extract(text)
('кот', 'от ', 'т с', ' си', 'сид', 'иде')
('Ко', 'от', 'т ', ' с', 'си', 'ид', 'де', 'ел')
('кот', 'сид', 'иде', 'дел', 'окн', 'кне', 'пёс', 'пол', 'олу')
Parameters¶
| Parameter | Type | Default | Description |
|---|---|---|---|
n |
int |
2 |
N-gram length in characters |
lowercase |
bool |
False |
Convert the text to lower case |
within_words |
bool |
False |
Take N-grams only inside words |
tokenizer |
Pattern / Callable |
None |
Word tokenizer for within_words or a regular expression; by default the tokenize method |
Methods¶
extract(text) extracts N-grams from a text.
| Parameter | Type | Default | Description |
|---|---|---|---|
text |
str |
- | Text string |
A text that is not a string raises SourceTypeError, and so does, with within_words, a tokenizer that cannot be called or does not return strings.
get_most_common(n=10) returns the top N-grams of the text as a list of (N-gram, frequency) pairs, the most frequent first.
| Parameter | Type | Default | Description |
|---|---|---|---|
n |
int |
10 |
Number of top N-grams |
A number that is not an integer of at least one raises ParameterError.
Warning
The method must be called after N-grams have been extracted with extract.
ce.get_most_common(2)
[(' на', 2), ('на ', 2)]