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- builtins.object
-
- ConnectiveIndices
class ConnectiveIndices(builtins.object) |
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ConnectiveIndices(nlp, language: str = 'es', descriptive_indices: text_complexity_analyzer_cm.coh_metrix_indices.descriptive_indices.DescriptiveIndices = None) -> None
This class will handle all operations to obtain the connective indices of a text according to Coh-Metrix
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Methods defined here:
- __init__(self, nlp, language: str = 'es', descriptive_indices: text_complexity_analyzer_cm.coh_metrix_indices.descriptive_indices.DescriptiveIndices = None) -> None
- The constructor will initialize this object that calculates the connective 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_additive_connectives_incidence(self, text: str, word_count: int = None, workers: int = -1) -> float
- This method returns the incidence per {self._incidence} words for additive connectives.
Parameters:
text(str): The text to be analyzed.
word_count(int): The amount of words in the text.
workers(int): Amount of threads that will complete this operation. If it's -1 then all cpu cores will be used.
Returns:
float: The incidence of additive connectives per {self._incidence} words.
- get_adversative_connectives_incidence(self, text: str, word_count: int = None, workers: int = -1) -> float
- This method returns the incidence per {self._incidence} words for adversative connectives.
Parameters:
text(str): The text to be analyzed.
word_count(int): The amount of words in the text.
workers(int): Amount of threads that will complete this operation. If it's -1 then all cpu cores will be used.
Returns:
float: The incidence of adversative connectives per {self._incidence} words.
- get_all_connectives_incidence(self, text: str, word_count: int = None, workers: int = -1) -> float
- This method returns the incidence per {self._incidence} words for all connectives.
Parameters:
text(str): The text to be analyzed.
word_count(int): The amount of words in the text.
workers(int): Amount of threads that will complete this operation. If it's -1 then all cpu cores will be used.
Returns:
float: The incidence of all connectives per {self._incidence} words.
- get_causal_connectives_incidence(self, text: str, word_count: int = None, workers: int = -1) -> float
- This method returns the incidence per {self._incidence} words for causal connectives.
Parameters:
text(str): The text to be analyzed.
word_count(int): The amount of words in the text.
workers(int): Amount of threads that will complete this operation. If it's -1 then all cpu cores will be used.
Returns:
float: The incidence of causal connectives per {self._incidence} words.
- get_logical_connectives_incidence(self, text: str, word_count: int = None, workers: int = -1) -> float
- This method returns the incidence per {self._incidence} words for logical connectives.
Parameters:
text(str): The text to be analyzed.
word_count(int): The amount of words in the text.
workers(int): Amount of threads that will complete this operation. If it's -1 then all cpu cores will be used.
Returns:
float: The incidence of logical connectives per {self._incidence} words.
- get_temporal_connectives_incidence(self, text: str, word_count: int = None, workers: int = -1) -> float
- This method returns the incidence per {self._incidence} words for temporal connectives.
Parameters:
text(str): The text to be analyzed.
word_count(int): The amount of words in the text.
workers(int): Amount of threads that will complete this operation. If it's -1 then all cpu cores will be used.
Returns:
float: The incidence of temporal connectives per {self._incidence} words.
Data descriptors defined here:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
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