# # ["ReEngage_LongActing_HighRiskMen_Nyanza","cpnSQ",2023,[1,2,3,4,5,6],[{"Risk": "HIGH"},{"Risk": "MEDIUM"}],"Male",20,29,[2023, 2025, 2099],[0,0.5,0.5],[0, 91, 92, 36500],[0.95, 0.95, 0, 0]] ] # And the points point_header, points = read_mat_points_file(tpi_matlab_filename) # We only take the first 3 points. Comment the following line to run the whole 250 points # points = points[0:3] # Create the default config builder config_builder = DTKConfigBuilder() # Set which executable we want to use for the experiments in the script #config_builder.set_experiment_executable('Eradication_2point7_20170405.exe') #config_builder.set_experiment_executable('Eradication_Memory_Plus_GH826.exe') config_builder.set_experiment_executable( 'EMOD_binary_20190402_broadcast_WouldHaveHadAIDS.exe') # This is REQUIRED by the templates config_builder.ignore_missing = True # Get the dicts points_dict = header_table_to_dict(point_header, points, index_name='TPI') for point in points_dict: tpi = point.pop('TPI') if 'TAGS' not in point: point['TAGS'] = {} point['TAGS']['TPI'] = tpi scenarios_dict = header_table_to_dict(scenario_header, scenarios)
] # And the points # point_header, points = read_mat_points_file(tpi_matlab_filename) # point_header, points = read_csv_points_file(tpi_csv_filename) points_df = read_csv_points_file(tpi_csv_filename) # We only take the first 3 points. Comment the following line to run the whole 250 points if JUST_TESTING: points_df = points_df[0:2] # Create the default config builder config_builder = DTKConfigBuilder() # Set which executable we want to use for the experiments in the script config_builder.set_experiment_executable( 'bin/20181022_EMOD_HIV_binary_with_relative_risk_factor.exe') # This is REQUIRED by the templates config_builder.ignore_missing = True # Get the dicts points_dict = header_table_to_dict(points_df, index_name='TPI') for point in points_dict: tpi = point.pop('TPI') if 'TAGS' not in point: point['TAGS'] = {} point['TAGS']['TPI'] = tpi with open('points_dict.json', 'w') as fp: json.dump(points_dict, fp)
# ['ART909090', "cpn5"], # ['ART100pct', "cpn6"] # And the points # point_header, points = read_mat_points_file(tpi_matlab_filename) point_header, points = read_csv_points_file(tpi_csv_filename) # We only take the first 3 points. Comment the following line to run the whole 250 points if JUST_TESTING: points = points[0:2] # Create the default config builder config_builder = DTKConfigBuilder() # Set which executable we want to use for the experiments in the script config_builder.set_experiment_executable( '..\Binary\EMOD_binary_20180921_with_configurable_ART.exe') # This is REQUIRED by the templates config_builder.ignore_missing = True # Get the dicts points_dict = header_table_to_dict(point_header, points, index_name='TPI') for point in points_dict: tpi = point.pop('TPI') if 'TAGS' not in point: point['TAGS'] = {} point['TAGS']['TPI'] = tpi with open('points_dict.json', 'w') as fp: json.dump(points_dict, fp)