Exemplo n.º 1
0
    def create_classification(self):

        sess = Database().session()

        sess.add(
            DBClassification(
                created_at=self.created_at,
                result=self.result,
            ))

        sess.commit()
        sess.close()
Exemplo n.º 2
0
    def count_predictions(label):
        """
        count all predictions or all predictions associated to a specific label made.
        :param label:
        :return: total amount of classifications
        """
        sess = Database().session()
        if label:

            rows = sess.query(
                func.count('*').filter(DBResult.label == "{label}".format(
                    label=label))).scalar()
        else:
            rows = sess.query(func.count(DBResult.result_id)).scalar()
        sess.close()
        return rows
Exemplo n.º 3
0
    def calc_accuracies():
        """
        Calculates the accuracy with which the class was predicted.
        :param label: the class with which the associated precisions of the classifications are calculated
        :return: accuracy of associated predictions
        """
        accuracies = {}
        sess = Database().session()
        for label in sess.query(DBResult.label):
            label = list(label)[0]
            acc_sum = sess.query(func.sum(DBResult.accuracy)).filter(
                DBResult.label == "{label}".format(label=label)).scalar()

            accuracies.update({
                label:
                round(acc_sum / DBClassification.count_predictions(label), 2)
            })

        sess.close()

        return accuracies
Exemplo n.º 4
0
    def total_predictions():
        """
        counts the number of predictions of the corresponding classes
        :return: The amount of predictions belong to each corresponding class
        """
        predictions = {}

        sess = Database().session()

        amounts = []
        for label in sess.query(DBResult.label):
            amounts.append(label)

        sess.close()
        predictions.update({
            list(label)[0]: amount
            for label, amount in Counter(amounts).items()
        })

        total_amount = reduce(lambda x, y: x + y, Counter(amounts).values())

        return predictions, total_amount
            print(f'404: File for Remiss {document.remiss_id} not found.')

        if f is not None:
            fp = BytesIO(f)
            FileManager.write_to_filepath(filepath, f)

    if FileManager.filepath_exists(filepath):
        fp = FileManager.get_filepath(filepath)
    else:
        continue

    try:
        list = DocumentParser.extract_list(fp)
    except (PDFTextExtractionNotAllowed, PDFSyntaxError):
        print(f'Document for Remiss {document.remiss_id} was not extracted.')
        continue

    if not list:
        print(f'Document for Remiss {document.remiss_id} was not extracted.')
        continue

    document.consultee_list = list

    Database.commit()

    print(f'Saved {len(list)} organisations for remiss {document.remiss_id}')

    fp.close()

Database.close()