fast_in_situ_calibration/Python/main.py

__author__ = "Olivier Vu thanh"
__email__ = "olivier.vu-thanh@grenoble-inp.org"

'''
Run "python main.py --config_file=config.json"

Available calibration methods are   : emwnenmf (EM-W-NeNMF from [quote paper])
                                    : coming soon...
'''

import numpy as np
import argparse
import json
from dataCreator import dataCreator
# from calibrationStatistics import calibrationStatistics
# from calibrationMethods.emwnenmf_updateinsideNNLS import emwnenmf
# from calibrationMethods.emwnenmf_seprestart import emwnenmf
from calibrationMethods.incal import incal
from calibrationMethods.emwnenmf import emwnenmf
from calibrationMethods.emwnenmf_comp import emwnenmf_comp
from calibrationMethods.emwnenmf_restart import emwnenmf_restart
from calibrationMethods.emwnenmf_break import emwnenmf_break
from calibrationMethods.emwamsgrad import emwamsgrad
from calibrationMethods.muem import muem
from calibrationMethods.emwfnnls import emwfnnls
from calibrationMethods.emwmunmf import emwmunmf
from calibrationMethods.emwnenmf_m import emwnenmf_m
from save2dat import save2dat


print('Work in progress')

'''
Get the config (json) file, see "config.json" for default one
'''
parser = argparse.ArgumentParser(description='Parse location of config file (json).')
parser.add_argument('--config_file', type=str, default='config.json',
                    help='path to json config file, see config.json for default')

args = parser.parse_args()
with open(args.config_file) as json_data_file:
    config = json.load(json_data_file)

'''
Main loop
'''

data = dataCreator(config['sceneWidth'],
                   config['sceneLength'],
                   config['numSensor'],
                   config['numRef'],
                   config['rdvR'],
                   config['mvR'],
                   config['phenLowerBound'],
                   config['phenUpperBound'],
                   config['Mu_beta'],
                   config['Mu_alpha'],
                   config['Bound_beta'],
                   config['Bound_alpha'])
m = data.numArea
n = data.numSensor + 1
RMSE = {}
T = {}
for method in config['calibrationMethods']:
    RMSE.update({method: []})
    T.update({method: []})

for run in range(config['numRuns']):
    data.create_scene(run+5)
    # ONLY EMWNENMF AND INCAL HAVE BEEN CODED FOR NOW
    print('run : ' + str(run))
    for method in config['calibrationMethods']:
        print('method : ' + method)
        calMethod = locals()[method]
        res = calMethod(data, data.Ginit, data.Finit, config['r'], config['Tmax'])
        if run == 0:
            RMSE[method] = res['RMSE']
            T[method] = res['T']
        else:
            RMSE[method] = np.vstack((RMSE[method], res['RMSE']))
            T[method] = np.vstack((T[method], res['T']))
        print('RMSE : ' + str(res['RMSE'][0][-1]) + '   ' + str(res['RMSE'][1][-1]))

if config['save2dat']:
    save2dat(RMSE, T, config['calibrationMethods'], config['numRuns'])