Python read_triplet_file Examples

Example #1

File: topic_clustering_sw_process.py Project: RedHenLab/CDI

def main():
    logging.basicConfig(level=logging.DEBUG)
    input_triplet_files = glob.glob('data/transformed_triplet_files_080819-081015/2008*.txt')
    input_triplet_files.sort()
    logging.debug('Files {0}'.format(len(input_triplet_files)))

    # Read in the triplets files, including the triplets and the time of the story
    original_documents = []
    for triplet_file in input_triplet_files:
        doc_tmp = readingfiles.read_triplet_file(triplet_file, use_ocr=True)
        if doc_tmp.filename != '' and doc_tmp.timestamp != '':
            original_documents.append(doc_tmp)
    logging.debug('Effective Files {0}'.format(len(original_documents)))

    # Train topic model
    model = topic_model.TopicModel(classifier_model_filename='preprocessing/model_segmenter.txt')
    model.feed(original_documents)

Example #2

def main():
    logging.basicConfig(level=logging.DEBUG)
    input_triplet_files = glob.glob(
        'data/transformed_triplet_files_080819-081015/2008*.txt')
    input_triplet_files.sort()
    logging.debug('Files {0}'.format(len(input_triplet_files)))

    # Read in the triplets files, including the triplets and the time of the story
    original_documents = []
    for triplet_file in input_triplet_files:
        doc_tmp = readingfiles.read_triplet_file(triplet_file, use_ocr=True)
        if doc_tmp.filename != '' and doc_tmp.timestamp != '':
            original_documents.append(doc_tmp)
    logging.debug('Effective Files {0}'.format(len(original_documents)))

    # Train topic model
    model = topic_model.TopicModel(
        classifier_model_filename='preprocessing/model_segmenter.txt')
    model.feed(original_documents)

Example #3

File: classifier.py Project: RedHenLab/CDI

 def train_from_files(self, input_triplet_files, category_list):
     corpus = topic_model._Corpus()
     for triplet_file in input_triplet_files:
         corpus.add_document(readingfiles.read_triplet_file(triplet_file, use_ocr=True))
     self.train_from_corpus(corpus, category_list)

Example #4

File: classifier.py Project: roshniRam/CDI

 def train_from_files(self, input_triplet_files, category_list):
     corpus = topic_model._Corpus()
     for triplet_file in input_triplet_files:
         corpus.add_document(
             readingfiles.read_triplet_file(triplet_file, use_ocr=True))
     self.train_from_corpus(corpus, category_list)