output = 'results/' + exp_name + '.csv'
l_scores = []
for args['set_id'] in range(1, 11):
for args['n'] in [1000, 5000]:
for args['citcio'] in [False, True]:
for args['n_epochs'] in [10, 402]:
for args['p'] in [5, 100]:
for args['prop_miss'] in [0, 0.1, 0.3]:
for args['model'] in ["dlvm", "lrmf"]:
t0 = time.time()
score = [ihdp_cevae(**args)]
args['time'] = int(time.time() - t0)
l_scores.append(
np.concatenate((list(args.values()), score)))
print('ihdp with ', args)
print('........... DONE')
print('in ', int(args["time"]), ' s \n\n')
score_data = pd.DataFrame(l_scores,
columns=list(args.keys()) +
l_tau)
score_data.to_csv(output + '_temp')
print('saving ' + exp_name + 'at: ' + output)
score_data.to_csv(output)
print('*' * 20)
print('IHDP with: ' + exp_name + ' succesfully ended.')
print('*' * 20)
#range_sig_prior = [0.1, 1, 10]
#range_n_epochs = [10, 200, 600]
exp_name = 'ihdp_mi'
#
args['m'] = 10
print('starting exp: ' + exp_name)
l_tau = ['tau_dr', 'tau_ols', 'tau_ols_ps']
output = 'results/2019-10-25_' + exp_name + '.csv'
l_scores = []
for args['set_id'] in range(1, 11):
for args['prop_miss'] in range_prop_miss:
t0 = time.time()
score = ihdp_mi(**args)
args['time'] = int(time.time() - t0)
l_scores.append(np.concatenate((list(args.values()), score)))
print('ihdp_mi with ', args)
print('........... DONE')
print('in ', int(args["time"]), ' s \n\n')
score_data = pd.DataFrame(l_scores, columns=list(args.keys()) + l_tau)
score_data.to_csv(output + '_temp')
print('saving ' + exp_name + 'at: ' + output)
score_data.to_csv(output)
print('*' * 20)
print('IHDP with: ' + exp_name + ' succesfully ended.')
print('*' * 20)
import numpy as np
import pandas as pd
import time
from main_ihdp import ihdp_miwae_save
from config_ihdp import args
# set here params
range_prop_miss = [0.1, 0.3, 0, 0.5]
exp_name = 'ihdp_save_12.1_11'
#
print('starting ihdp: ' + exp_name)
args_col = list(set(args.keys()) - set(['set_id']))
args = {k: args[k] for k in args_col}
args['set_id_range'] = range(1,2)
args['sig_prior'] = 1
args['d_miwae'] = 5
args['n_epochs'] = 100
score_data = pd.DataFrame()
for args['prop_miss'] in range_prop_miss:
if args['prop_miss'] == 0.5:
args['sig_prior'] = 0.1
args['d_miwae'] = 5
t0 = time.time()
score = ihdp_miwae_save(out_folder = 'results/',**args)
args['time'] = int(time.time() - t0)
print('ihdp with ', args, '(',score,')')
range_sig_prior = [0.1, 1, 10]
range_n_epochs = [100,] #[10,]# 400]
range_d_miwae = [5, 10, 100]
exp_name = 'ihdp_cv_10.2_11'
#
print('starting ihdp: ' + exp_name)
l_elbo = ['d_miwae', 'sig_prior', 'k', 'elbo']
output = 'results/'+exp_name+'.csv'
l_scores = []
args_col = list(set(args.keys()) - set(['sig_prior','d_miwae']))
args = {k: args[k] for k in args_col}
args['k_fold'] = 5
for args['set_id'] in range(1,1001, 100):
for args['prop_miss'] in range_prop_miss:
for args['add_wy'] in [False]:#, True]:
for args['n_epochs'] in range_n_epochs:
t0 = time.time()
score = ihdp_miwae_cv(**args, sig_prior_list = range_sig_prior, d_miwae_list = range_d_miwae)
args['time'] = int(time.time() - t0)
for i in range(len(score)):
l_scores.append(np.concatenate((list(args.values()),score[i])))
print('ihdp with ', args)
print('........... DONE')
print('in ', int(args["time"]) , ' s \n\n')
# set here params
range_prop_miss = [
0.5,
] #[0.1, 0.3, 0]
exp_name = 'ihdp_08.2_11_cevae'
#
print('starting ihdp: ' + exp_name)
l_tau = ['tau_cevae']
output = 'results/' + exp_name + '.csv'
l_scores = []
args['n_epochs'] = 100
args_col = list(set(args.keys()) - set(['set_id_range']))
args = {k: args[k] for k in args_col}
for args['set_id'] in range(1, 1001):
for args['prop_miss'] in range_prop_miss:
t0 = time.time()
score = ihdp_cevae(**args)
args['time'] = int(time.time() - t0)
l_scores.append(np.concatenate((list(args.values()), [score])))
print('ihdp with ', args)
print('........... DONE')
print('in ', int(args["time"]), ' s \n\n')
score_data = pd.DataFrame(l_scores, columns=list(args.keys()) + l_tau)
score_data.to_csv(output + '_temp')