exp_cevae.py

import numpy as np
import pandas as pd
import time

from main import exp_cevae
from config import args


range_seed = np.arange(2)
range_n = [1000]
range_p = [20, 100, 1000]
range_prop_miss = [0.1, 0.3, 0]
range_n_epochs = [10, 200, 600]

exp_name = 'exp_cevae_0'
# 


print('starting exp: ' + exp_name)
l_tau = ['tau_dr', 'tau_dr_ps']
output = 'results/'+exp_name+'.csv'
l_scores = []

for args['model'] in ["dlvm","lrmf"]:
    for args['seed'] in range_seed:
        for args['n_epochs'] in range_n_epochs:
            for args['prop_miss'] in range_prop_miss:
                for args['n'] in range_n:
                    for args['p'] in range_p:     
                    
                        t0 = time.time()
                        score = exp_cevae(**args)
                        args['time'] = int(time.time() - t0)
                        l_scores.append(np.concatenate((list(args.values()),score)))
                        print('exp 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('Exp: '+ exp_name+' succesfully ended.')
print('*'*20)