mainDatasetSplitter.py

import os
import sys

from preprocessing.PreprocessorNZ import PreprocessorNZ
from utils.DatasetOptions import DatasetOptions
from utils.DatasetSplitter import DatasetSplitter

dirProject = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) + '/';
dirData = dirProject + 'data/';

new_features = ['previous_visits', 'ratio_los_age', 'ratio_numDK_age', 'ratio_los_numDK', 'ratio_numCHOP_age',
                'ratio_los_numOE', 'ratio_numOE_age', 'mult_los_numCHOP', 'mult_equalOE_numDK',
                'diff_drg_alos', 'diff_drg_lowerbound', 'diff_drg_upperbound',
                'rel_diff_drg_alos', 'rel_diff_drg_lowerbound', 'rel_diff_drg_upperbound',
                'alos', 'ratio_drg_los_alos'];

def main(dict_dataset_options):

    options = DatasetOptions(dict_dataset_options);
    preproc = PreprocessorNZ(options);

    print('grouping: ' + str(options.getGroupingName()))
    # preproc.processDischargeFile();
    # preproc.processDiagnosisFile();

    preproc.createFeatureSet();
    preproc.encodeFeatures();
    preproc.fuse();




if __name__ == '__main__':
    if len(sys.argv) > 1:
        year_to_process = int(sys.argv[1]);
    else:
        year_to_process = 1988;

    dict_dataset_options = {
        'dir_data':             dirData,
        'data_prefix':          'nz',
        'dataset':              '20072017',
        'encoding':             'embedding',
        'grouping':             'verylightgrouping',
        'newfeatures':          None,
        'featurereduction':     {'method': 'FUSION'}
    }

    options = DatasetOptions(dict_dataset_options);

    dataset_splitter = DatasetSplitter(options);

    dataset_splitter.splitDatasetIntoTrainingTesting()