Source code for annotations.ReOccurrences.sppasreocc

# -*- coding: UTF-8 -*-
:author:   Brigitte Bigi
:summary:  SPPAS integration of ReOccurrences automatic annotation

.. _This file is part of SPPAS: <>

     ___   __    __    __    ___
    /     |  \  |  \  |  \  /              the automatic
    \__   |__/  |__/  |___| \__             annotation and
       \  |     |     |   |    \             analysis
    ___/  |     |     |   | ___/              of speech

    Copyright (C) 2011-2021  Brigitte Bigi
    Laboratoire Parole et Langage, Aix-en-Provence, France

    Use of this software is governed by the GNU Public License, version 3.

    SPPAS is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
    the Free Software Foundation, either version 3 of the License, or
    (at your option) any later version.

    SPPAS is distributed in the hope that it will be useful,
    but WITHOUT ANY WARRANTY; without even the implied warranty of
    GNU General Public License for more details.

    You should have received a copy of the GNU General Public License
    along with SPPAS. If not, see <>.

    This banner notice must not be removed.



import logging

from sppas.src.config import IndexRangeException
from sppas.src.config import sppasUnicode
from sppas.src.anndata import sppasTrsRW
from sppas.src.anndata import sppasTranscription

from ..annotationsexc import AnnotationOptionError
from ..annotationsexc import EmptyOutputError
from ..annotationsexc import NoTierInputError
from ..baseannot import sppasBaseAnnotation

from .reoccurrences import ReOccurences
from .reoccset import sppasAnnReOccSet

# ----------------------------------------------------------------------------

[docs]class sppasReOcc(sppasBaseAnnotation): """SPPAS integration of the automatic re-occurrences annotation. """
[docs] def __init__(self, log=None): """Create a new sppasReOcc instance with only the general rules. :param log: (sppasLog) Human-readable logs. """ super(sppasReOcc, self).__init__("reoccurrences.json", log) self.__reocc = ReOccurences() self.max_span = 20
# ----------------------------------------------------------------------- # Methods to fix options # -----------------------------------------------------------------------
[docs] def fix_options(self, options): """Fix all options. Available options are: :param options: (sppasOption) """ for opt in options: key = opt.get_key() if "tiername" == key: self.set_tiername(opt.get_value()) elif "span" == key: self.set_span(opt.get_value()) elif "pattern" in key: self._options[key] = opt.get_value() else: raise AnnotationOptionError(key)
# ----------------------------------------------------------------------- # Getters and Setters # -----------------------------------------------------------------------
[docs] def set_tiername(self, tier_name): """Fix the tiername option. :param tier_name: (str) """ self._options['tiername'] = sppasUnicode(tier_name).to_strip()
# -----------------------------------------------------------------------
[docs] def set_span(self, span): """Fix the span option. Span is the maximum number of annotations to search for re-occ. A value of 1 means to search only in the next annotation. :param span: (int) Value between 1 and 20 """ span = int(span) if 0 < span <= self.max_span: self._options['span'] = span else: raise IndexRangeException(span, 0, self.max_span)
# ---------------------------------------------------------------------- # The search for re-occurrences is here # ----------------------------------------------------------------------
[docs] def detection(self, tier_spk1, tier_spk2): """Search for the re-occurrences of annotations. :param tier_spk1: (sppasTier) :param tier_spk2: (sppasTier) """ annset = sppasAnnReOccSet() if tier_spk1.is_float(): tier_spk1.set_radius(0.04) if tier_spk1.is_float(): tier_spk2.set_radius(0.04) end_loc = tier_spk2[-1].get_highest_localization() for ann1 in tier_spk1: # Localization of the end of the current annotation of spk1 cur_loc = ann1.get_highest_localization() # Search for the annotations of spk2 after this localization all_anns2 = tier_spk2.find(cur_loc, end_loc, overlaps=False) # Select only the next N annotations of spk2 window_size = min(len(all_anns2), self._options["span"]) anns2 = all_anns2[:window_size] # Search for the re-occurring labels of annotations # ------------------------------------------------- reoccs = self.__reocc.eval(ann1, anns2) if len(reoccs) > 0: annset.append(ann1, reoccs) return annset.to_tier()
# ---------------------------------------------------------------------- # Apply the annotation on a given file # -----------------------------------------------------------------------
[docs] def get_inputs(self, input_files): """Return 2 tiers with name given in options. :param input_files: (list) :raise: NoTierInputError :return: (sppasTier) """ if len(input_files) != 2: raise Exception("Invalid format of input files.") tier_src = None for filename in input_files[0]: parser = sppasTrsRW(filename) trs_input = if tier_src is None: tier_src = trs_input.find(self._options['tiername'], case_sensitive=False) if tier_src is None: logging.error("A source tier with time-aligned items was expected but not found.") raise NoTierInputError tier_echo = None for filename in input_files[1]: parser = sppasTrsRW(filename) trs_input = if tier_echo is None: tier_echo = trs_input.find(self._options['tiername'], case_sensitive=False) if tier_echo is None: logging.error("An echo tier with time-aligned items was expected but not found.") raise NoTierInputError return tier_src, tier_echo
# -----------------------------------------------------------------------
[docs] def run(self, input_files, output=None): """Run the automatic annotation process on an input. Input file is a tuple with 2 files: the main speaker and the echoing speaker. :param input_files: (list of list of str) Time-aligned items, Time-aligned items :param output: (str) the output name :returns: (sppasTranscription) """ # Get the tiers to be used tier_spk1, tier_spk2 = self.get_inputs(input_files) # Re-occurrences Automatic Detection new_tiers = self.detection(tier_spk1, tier_spk2) # Create the transcription result trs_output = sppasTranscription( trs_output.set_meta('annotation_result_of', input_files[0][0]) for tier in new_tiers: trs_output.append(tier) # Save in a file if output is not None: if len(trs_output) > 0: output_file = self.fix_out_file_ext(output) parser = sppasTrsRW(output_file) parser.write(trs_output) # self.print_filename(output_file) return [output_file] else: raise EmptyOutputError return trs_output
# ----------------------------------------------------------------------
[docs] def get_output_pattern(self): """Pattern this annotation uses in an output filename.""" return self._options.get("outputpattern", "-reocc")