class_docstr: Scans Greek texts that already contain macronized
  (i.e., long and shorts) texts.
class_docstr_tok: ["Scans","Greek","texts","that","already","contain","macronized","(","i.e.",",","long","and","shorts",")","texts","."]
docstr: Reduce a list of ``[sentence[word[syllable]]]`` to ``[sentence[syllable]]``.
  
  Args:
      words_syllables: List of syllables
  
  Returns:
      List of words
  
  >>> from cltk.prosody.grc import Scansion
  >>> input_syllables = [[["νε", "ος"], ["μεν"], ["και"], ["α", "πει", "ρος"], ["δι", "κων"], ["ε", "γω", "γε"], ["ε", "τι"]], [["μεν"], ["και"], ["α", "πει", "ρος"]]]
  >>> Scansion()._syllable_condenser(input_syllables)
  [['νε', 'ος', 'μεν', 'και', 'α', 'πει', 'ρος', 'δι', 'κων', 'ε', 'γω', 'γε', 'ε', 'τι'], ['μεν', 'και', 'α', 'πει', 'ρος']]
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code: def _syllable_condenser(
      words_syllables: List[List[List[str]]],
  ) -> List[List[str]]:
      """Reduce a list of ``[sentence[word[syllable]]]`` to ``[sentence[syllable]]``.
  
      Args:
          words_syllables: List of syllables
  
      Returns:
          List of words
  
      >>> from cltk.prosody.grc import Scansion
      >>> input_syllables = [[["νε", "ος"], ["μεν"], ["και"], ["α", "πει", "ρος"], ["δι", "κων"], ["ε", "γω", "γε"], ["ε", "τι"]], [["μεν"], ["και"], ["α", "πει", "ρος"]]]
      >>> Scansion()._syllable_condenser(input_syllables)
      [['νε', 'ος', 'μεν', 'και', 'α', 'πει', 'ρος', 'δι', 'κων', 'ε', 'γω', 'γε', 'ε', 'τι'], ['μεν', 'και', 'α', 'πει', 'ρος']]
      """
      sentences_syllables = list()
      for sentence in words_syllables:
          syllables_sentence = list()  # type: List[str]
          for word in sentence:
              syllables_sentence += word
          sentences_syllables.append(syllables_sentence)
      return sentences_syllables
  
file_path: cltk/src/cltk/prosody/grc.py
imports: from typing import List
  from cltk.core.cltk_logger import logger
label_desc: Use image node_id 6 for calling the Scansion obj's underlying member method code with example usage: obj._syllable_condenser(words_syllables) and returns: sentences_syllables