/
create_patients.py
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/
create_patients.py
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import os
import sys
import shutil
import classes.sim as sim
import pickle as pkl
import argparse
DEFAULT_RUN_NAME = 'TEST'
def run(run_name=DEFAULT_RUN_NAME, trials=5, patient_count=2000,
num_effects=[1, 2, 4, 8], observed_variables=[50], per_effect=[5],
effect_mag=[1], sim_model=1, systematic_bias=0.1, input_variance=0.1,
missing_data=0):
i = 0
patients_list = []
for effects in num_effects:
for ov in observed_variables:
# for pe in per_effect:
for mag in effect_mag:
for trial in range(trials):
patients = sim.create_patients(patient_count=patient_count,
observed_variables=ov,
systematic_bias=systematic_bias,
input_variance=input_variance,
effects=effects,
per_effect=per_effect,
effect_mag=mag,
trial=trial,
sim_model=sim_model,
missing_data=missing_data)
file_name = ('./data/' + run_name + '/patients/' +
str(sim_model) + '_' + str(effects) + '_' +
str(per_effect) + '_' + str(mag) + '_' +
str(ov) + '_' + str(trial) + '.p')
pkl.dump(patients, open(file_name, "wb"),
protocol=2)
del patients
print(i)
i += 1
def create_directories(run_name):
data_path = 'data'
if not os.path.exists(data_path):
os.makedirs(data_path)
run_path = data_path + '/' + run_name
if os.path.exists(run_path):
shutil.rmtree(run_path)
os.makedirs(run_path)
patients_path = run_path + '/patients'
os.makedirs(patients_path)
score_path = run_path + '/scores'
os.makedirs(score_path)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
# defaults are quick run
parser.add_argument("--run_name", help="name the run")
parser.add_argument("--trials", nargs='?', default=1,
help="number of independent replicates")
parser.add_argument("--patient_count", nargs='?', default=100,
help="number of patient")
parser.add_argument("--num_effects", nargs='*', help="""number of hidden
input effects (list of ints)""")
parser.add_argument("--observed_variables", nargs='*', default=400,
help="observed variables per patient")
parser.add_argument("--per_effect", nargs='?', default=5,
help="Number of clincial variables affected by hidden")
parser.add_argument("--effect_mag", nargs='*',
help="Effect magnitude range (x input variance)")
parser.add_argument("--sim_model", nargs='?', default=1,
help=""" - all or none hidden effects,
2 - continous (percent hidden = perecent case,
3 - rules based """)
parser.add_argument("--systematic_bias", nargs='?', default=0.1,
help="""bias amount assessed randomly to half of the
patients (0 for none)""")
parser.add_argument("--input_variance", nargs='?', default=0.1,
help="variance per variable")
parser.add_argument("--missing_data", nargs='?', default=0,
help="Perecentage of data to be missing (randomly)")
args = parser.parse_args()
if args.observed_variables is None:
args.observed_variables = [50, 100, 200]
else:
args.observed_variables = [int(x) for x in args.observed_variables]
if args.num_effects is None:
args.num_effects = [1, 2, 4, 8]
else:
args.num_effects = [int(x) for x in args.num_effects]
if args.effect_mag is None:
args.effect_mag = [1, 2, 4]
else:
args.effect_mag = [int(x) for x in args.effect_mag]
if args.run_name is None:
args.run_name = DEFAULT_RUN_NAME
create_directories(args.run_name)
target = open('./data/' + args.run_name + '/args.txt', 'w+')
target.write(str(args))
target.truncate()
target.close()
print(args)
args.sim_model = int(args.sim_model)
run(run_name=args.run_name,
trials=int(args.trials),
patient_count=int(args.patient_count),
num_effects=args.num_effects,
observed_variables=args.observed_variables,
per_effect=int(args.per_effect),
effect_mag=args.effect_mag,
sim_model=int(args.sim_model),
systematic_bias=float(args.systematic_bias),
input_variance=float(args.input_variance),
missing_data=float(args.missing_data))