src.dackar.text_processing.SpellChecker
=======================================

.. py:module:: src.dackar.text_processing.SpellChecker

.. autoapi-nested-parse::

   Created on October, 2022

   @author: mandd, wangc



Attributes
----------

.. autoapisummary::

   src.dackar.text_processing.SpellChecker.logger


Classes
-------

.. autoapisummary::

   src.dackar.text_processing.SpellChecker.SpellChecker


Module Contents
---------------

.. py:data:: logger

.. py:class:: SpellChecker(checker='autocorrect')

   Bases: :py:obj:`object`


   Object to find misspelled words and automatically correct spelling

   Note: when using autocorrect, one need to conduct a spell test to identify the threshold (the word frequencies)


   .. py:attribute:: checker
      :value: ''



   .. py:attribute:: addedWords
      :value: []



   .. py:attribute:: includedWords
      :value: []



   .. py:method:: addWordsToDictionary(words)

      Adds a list of words to the spell check dictionary

      :param words: list, list of words to add to the dictionary

      :returns: None



   .. py:method:: getMisspelledWords(text)

      Returns a list of words that are misspelled according to the dictionary used

      :param None:

      :returns: list, list of misspelled words
      :rtype: misspelled



   .. py:method:: correct(text)

      Performs automatic spelling correction and returns corrected text

      :param None:

      :returns: str, spelling corrected text
      :rtype: corrected



   .. py:method:: handleAbbreviations(abbrDatabase, text, type)

      Performs automatic correction of abbreviations and returns corrected text
      This method relies on a database of abbreviations located at:
      `src/nlp/data/abbreviations.xlsx`
      This database contains the most common abbreviations collected from literature and
      it provides for each abbreviation its corresponding full word(s); an abbreviation might
      have multiple words associated. In such case the full word that makes more sense given the
      context is chosen (see findOptimalOption method)

      :param abbrDatabase: pandas dataframe, dataframe containing library of abbreviations
      :param and their corresponding full expression:
      :param text: str, string of text that will be analyzed
      :param type: string, type of abbreviation method ('spellcheck','hard','mixed') that are employed
      :param to determine which words are abbreviations that need to be expanded:
      :param \* spellcheck: in this case spellchecker is used to identify words that
      :param are not recognized:
      :param \* hard: here we directly search for the abbreviations in the provided
      :param sentence:
      :param \* mixed: here we perform first a "hard" search followed by a "spellcheck"
      :param search:

      :returns: list, list of corrected text options
      :rtype: options



   .. py:method:: generateAbbrDict(abbrDatabase)

      Generates an AbbrDict that can be used by handleAbbreviationsDict

      :param abbrDatabase: pandas dataframe, dataframe containing library of abbreviations
      :param and their corresponding full expression:

      :returns: dictionary, a abbreviations dictionary
      :rtype: abbrDict



   .. py:method:: handleAbbreviationsDict(abbrDict, text, type)

      Performs automatic correction of abbreviations and returns corrected text
      This method relies on a database of abbreviations located at:
      src/nlp/data/abbreviations.xlsx
      This database contains the most common abbreviations collected from literature and
      it provides for each abbreviation its corresponding full word(s); an abbreviation might
      have multple words associated. In such case the full word that makes more sense given the
      context is chosen (see findOptimalOption method)

      :param abbrDict: dictionary, dictionary containing library of abbreviations
      :param and their corresponding full expression:
      :param text: str, string of text that will be analyzed
      :param type: string, type of abbreviation method ('spellcheck','hard','mixed') that are employed
      :param to determine which words are abbreviations that need to be expanded:
      :param \* spellcheck: in this case spellchecker is used to identify words that
      :param are not recognized:
      :param \* hard: here we directly search for the abbreviations in the provided
      :param sentence:
      :param \* mixed: here we perform first a "hard" search followed by a "spellcheck"
      :param search:

      :returns: list, list of corrected text options
      :rtype: options



   .. py:method:: findOptimalOption(options)

      Method to handle abbreviation with multiple meanings

      :param options: list, list of sentence options

      :returns: string, option from the provided options list that fits more the
                possible
      :rtype: optimalOpt