# # ["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)
