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generate_predictions.py
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generate_predictions.py
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"""
Script to generate predictions from simulator for closed_loop_oed simulations
Peter Attia
Last updated August 23, 2018
"""
import numpy as np
import argparse
from sim_with_seed import sim
import os
class GetRewards(object):
def __init__(self, args):
self.batch_file = os.path.join(args.data_dir, args.batch_dir, str(args.round_idx) + '.csv')
self.pred_file = os.path.join(args.data_dir, args.pred_dir, str(args.round_idx) + '.csv') # note this is for previous round
self.sim_mode = args.sim_mode
self.round_idx = args.round_idx
self.seed = args.seed
pass
def run(self):
batch_file = self.batch_file
pred_file = self.pred_file
sim_mode = self.sim_mode
round_idx = self.round_idx
seed = self.seed
# Read in new policies
policies = np.genfromtxt(batch_file, delimiter=',')
# Generate predictions
pol_w_lifetimes = np.zeros((len(policies),5))
for k, policy in enumerate(policies):
C1 = policy[0]
C2 = policy[1]
C3 = policy[2]
C4 = 0.2/(1/6 - (0.2/C1 + 0.2/C2 + 0.2/C3))
lifetime = sim(C1, C2, C3, sim_mode,seed=seed+10*round_idx)
pol_w_lifetimes[k,:]= [C1,C2,C3,C4,lifetime]
# Remove one or two policies
if np.random.random()>0.5:
pol_w_lifetimes = np.delete(pol_w_lifetimes, (-1), axis=0)
if np.random.random()>0.5:
pol_w_lifetimes = np.delete(pol_w_lifetimes, (-1), axis=0)
# Save predictions to pred/<round_idx>.csv
np.savetxt(pred_file,pol_w_lifetimes,delimiter=',', fmt='%1.3f')
def parse_args():
"""
Specifies command line arguments for the program.
"""
parser = argparse.ArgumentParser(description='Generate predictions using thermal simulator')
parser.add_argument('--data_dir', nargs='?', default='data_hpsims/')
parser.add_argument('--pred_dir', nargs='?', default='pred/')
parser.add_argument('--batch_dir', nargs='?', default='batch/')
parser.add_argument('--round_idx', default=0, type=int)
parser.add_argument('--seed', default=0, type=int,
help='Seed for random number generators')
parser.add_argument('--sim_mode', nargs='?', default='hi')
return parser.parse_args()
def main():
args = parse_args()
np.random.seed(args.seed+10*args.round_idx)
np.set_printoptions(threshold=np.inf)
assert (os.path.exists(os.path.join(args.data_dir, args.pred_dir)))
assert (os.path.exists(os.path.join(args.data_dir, args.batch_dir)))
agent = GetRewards(args)
agent.run()
if __name__ == '__main__':
main()