'''
Created on Jul 4, 2017

@author: David
'''

import numpy as np
import cPickle as pickle
from sklearn.neural_network import MLPClassifier

data = []
labels = []

def train_classifier(data_file, hidden_layers, learning_rate):
    with open(data_file, "r") as f:
        for l in f:
            if l.startswith("@"):
                continue
            if not l.strip():
                continue
            values,target = l.rstrip().rsplit(",", 1)
            values = np.array(values.split(","), dtype='float64')
            data.append(values)
            labels.append(target)
    
    pname = data_file+"-mlp-"+"_".join([str(x) for x in hidden_layers])+"_"+str(learning_rate)+".pickle"
    
    print(pname)
         
    classifier = MLPClassifier(hidden_layer_sizes=hidden_layers, max_iter=1000, learning_rate_init=learning_rate)
    classifier.fit(data,labels)
    
    pickle.dump(classifier, open(pname, "wb"), protocol=2)
    return pname