Modules
		multiprocessing spacy statistics

Classes
		builtins.object ReferentialCohesionIndices   class ReferentialCohesionIndices(builtins.object)     ReferentialCohesionIndices(nlp, language: str = 'es') -> None   This class will handle all operations to find the synthactic pattern density indices of a text according to Coh-Metrix.     Methods defined here: __init__(self, nlp, language: str = 'es') -> None The constructor will initialize this object that calculates the synthactic pattern density indices for a specific language of those that are available.   Parameters: nlp: The spacy model that corresponds to a language. language(str): The language that the texts to process will have.   Returns: None. get_anaphore_overlap_adjacent_sentences(self, text: str, workers: int = -1) -> float This method calculates the mean of the anaphore overlap for adjacent sentences in a text.   Parameters: text(str): The text to be analyzed. workers(int): Amount of threads that will complete this operation. If it's -1 then all cpu cores will be used.   Returns: float: The mean mean of the anaphore overlap. get_anaphore_overlap_all_sentences(self, text: str, workers: int = -1) -> float This method calculates the mean of the anaphore overlap for all sentences in a text.   Parameters: text(str): The text to be analyzed. workers(int): Amount of threads that will complete this operation. If it's -1 then all cpu cores will be used.   Returns: float: The mean mean of the anaphore overlap. get_argument_overlap_adjacent_sentences(self, text: str, workers: int = -1) -> float This method calculates the argument overlap for adjacent sentences in a text.   Parameters: text(str): The text to be analyzed. workers(int): Amount of threads that will complete this operation. If it's -1 then all cpu cores will be used.   Returns: float: The mean argument overlap. get_argument_overlap_all_sentences(self, text: str, workers: int = -1) -> float This method calculates the argument overlap for all sentences in a text.   Parameters: text(str): The text to be analyzed. workers(int): Amount of threads that will complete this operation. If it's -1 then all cpu cores will be used.   Returns: float: The mean argument overlap. get_content_word_overlap_adjacent_sentences(self, text: str, workers: int = -1) -> float This method calculates the mean and standard deviation of the content word overlap for adjacent sentences in a text.   Parameters: text(str): The text to be analyzed. workers(int): Amount of threads that will complete this operation. If it's -1 then all cpu cores will be used.   Returns: float: The mean mean and standard deviation of the content word overlap. get_content_word_overlap_all_sentences(self, text: str, workers: int = -1) -> text_complexity_analyzer_cm.utils.statistics_results.StatisticsResults This method calculates the mean and standard deviation of the content word overlap for all sentences in a text.   Parameters: text(str): The text to be analyzed. workers(int): Amount of threads that will complete this operation. If it's -1 then all cpu cores will be used.   Returns: StatisticsResults: The mean mean and standard deviation of the content word overlap. get_noun_overlap_adjacent_sentences(self, text: str, workers: int = -1) -> float This method calculates the noun overlap for adjacent sentences in a text.   Parameters: text(str): The text to be analyzed. workers(int): Amount of threads that will complete this operation. If it's -1 then all cpu cores will be used.   Returns: float: The mean noun overlap. get_noun_overlap_all_sentences(self, text: str, workers: int = -1) -> float This method calculates the noun overlap for all sentences in a text.   Parameters: text(str): The text to be analyzed. workers(int): Amount of threads that will complete this operation. If it's -1 then all cpu cores will be used.   Returns: float: The mean noun overlap. get_stem_overlap_adjacent_sentences(self, text: str, workers: int = -1) -> float This method calculates the stem overlap for adjacent sentences in a text.   Parameters: text(str): The text to be analyzed. workers(int): Amount of threads that will complete this operation. If it's -1 then all cpu cores will be used.   Returns: float: The mean stem overlap. get_stem_overlap_all_sentences(self, text: str, workers: int = -1) -> float This method calculates the stem overlap for all sentences in a text.   Parameters: text(str): The text to be analyzed. workers(int): Amount of threads that will complete this operation. If it's -1 then all cpu cores will be used.   Returns: float: The mean stem overlap. Data descriptors defined here: __dict__ dictionary for instance variables (if defined) __weakref__ list of weak references to the object (if defined)

Functions
		analyze_anaphore_overlap(prev_sentence: spacy.tokens.span.Span, cur_sentence: spacy.tokens.span.Span, language: str = 'es') -> int This function analyzes whether or not there's anaphore overlap between two sentences.   Parameters: prev_sentence(Span): The previous sentence to analyze. cur_sentence(Span): The current sentence to analyze. language(str): The language of the sentences.   Returns: int: 1 if there's overlap between the two sentences and 0 if no. analyze_argument_overlap(prev_sentence: spacy.tokens.span.Span, cur_sentence: spacy.tokens.span.Span, language: str = 'es') -> int This function analyzes whether or not there's argument overlap between two sentences.   Parameters: prev_sentence(Span): The previous sentence to analyze. cur_sentence(Span): The current sentence to analyze. language(str): The language of the sentences.   Returns: int: 1 if there's overlap between the two sentences and 0 if no. analyze_content_word_overlap(prev_sentence: spacy.tokens.span.Span, cur_sentence: spacy.tokens.span.Span, language='es') -> float This function calculates the proportional content word overlap between two sentences.   Parameters: prev_sentence(Span): The previous sentence to analyze. cur_sentence(Span): The current sentence to analyze. language(str): The language of the sentences.   Returns: float: Proportion of tokens that overlap between the current and previous sentences analyze_noun_overlap(prev_sentence: spacy.tokens.span.Span, cur_sentence: spacy.tokens.span.Span, language: str = 'es') -> int This function analyzes whether or not there's noun overlap between two sentences for a language.   Parameters: prev_sentence(Span): The previous sentence to analyze. cur_sentence(Span): The current sentence to analyze. language(str): The language of the sentences.   Returns: int: 1 if there's overlap between the two sentences and 0 if no. analyze_stem_overlap(prev_sentence: spacy.tokens.span.Span, cur_sentence: spacy.tokens.span.Span, language: str = 'es') -> int This function analyzes whether or not there's stem overlap between two sentences.   Parameters: prev_sentence(Span): The previous sentence to analyze. cur_sentence(Span): The current sentence to analyze. language(str): The language of the sentences.   Returns: int: 1 if there's overlap between the two sentences and 0 if no.

Data
		ACCEPTED_LANGUAGES = {'es': 'es_core_news_lg'} Callable = typing.Callable List = typing.List