"""Entry-point script to label radiology reports."""

import pandas as pd

from args import ArgParser

from loader import Loader

from stages import Extractor, Classifier, Aggregator

from constants import *

def write(reports, labels, output_path, verbose=False):

    """Write labeled reports to specified path."""

    labeled_reports = pd.DataFrame({REPORTS: reports})

    for index, category in enumerate(CATEGORIES):

        labeled_reports[category] = labels[:, index]

    if verbose:

        print(f"Writing reports and labels to {output_path}.")

    labeled_reports[[REPORTS] + CATEGORIES].to_csv(output_path,

                                                   index=False)

def label(args):

    """Label the provided report(s)."""

    loader = Loader(args.reports_path,

                    args.sections_to_extract,

                    args.extract_strict)

    extractor = Extractor(args.mention_phrases_dir,

                          args.unmention_phrases_dir,

                          verbose=args.verbose)

    classifier = Classifier(args.pre_negation_uncertainty_path,

                            args.negation_path,

                            args.post_negation_uncertainty_path,

                            verbose=args.verbose)

    aggregator = Aggregator(CATEGORIES,

                            verbose=args.verbose)

    # Load reports in place.

    loader.load()

    # Extract observation mentions in place.

    extractor.extract(loader.collection)

    # Classify mentions in place.

    classifier.classify(loader.collection)

    # Aggregate mentions to obtain one set of labels for each report.

    labels = aggregator.aggregate(loader.collection)

    write(loader.reports, labels, args.output_path, args.verbose)

if __name__ == "__main__":

    parser = ArgParser()

    label(parser.parse_args())