def training_round_script():
glob_const=globalconstants.GlobalConstants();
init_set(glob_const);
SNRval=0.5;
#training_round_list=[];
training_round_list=range(2,15);
training_acc=[];
testing_acc=[];
rounds_tillnow=[];
pos_tr_eg=glob_const.no_pos_training_eg;
neg_tr_eg=glob_const.no_neg_training_eg;
pos_te_eg=glob_const.no_pos_testing_eg;
neg_te_eg=glob_const.no_neg_testing_eg;
for training_round in training_round_list:
boost=adaboost_train_test.AdaBoostTrainTest(SNRval,training_round,\
pos_tr_eg,neg_tr_eg,pos_te_eg,neg_te_eg);
boost.train_adaboost();
boost.test_adaboost();
training_acc.append(boost.training_accuracy);
testing_acc.append(boost.testing_accuracy);
rounds_tillnow.append(training_round);
#this now saves the file at every iteration
#if you want to quit the program before it finishes
vid_utils.savefile(rounds_tillnow,training_acc,'data/adaboost_training_acc.txt')
vid_utils.savefile(rounds_tillnow,testing_acc,'data/adaboost_testing_acc.txt')
plt.plot(training_round_list,training_acc,'bo-',label='Training Accuracy');
plt.plot(training_round_list,testing_acc,'ro-',label='Testing Accuracy');
plt.legend();
plt.show();
def exampleno_script():
glob_const = globalconstants.GlobalConstants()
init_set(glob_const)
SNRval = 0.5
#exampleno_list=[];
exampleno_list = range(50, 1000, 50)
training_acc = []
testing_acc = []
list_tillnow = []
time_list = []
training_rounds = 15
pos_te_eg = glob_const.no_pos_testing_eg
neg_te_eg = glob_const.no_neg_testing_eg
for exampleno in exampleno_list:
starttime = time.time()
glob_const.no_pos_training_eg = exampleno
glob_const.no_neg_training_eg = exampleno
glob_const.savefile()
boost=adaboost_train_test.AdaBoostTrainTest(SNRval,training_rounds,\
exampleno,exampleno,pos_te_eg,neg_te_eg)
boost.train_adaboost()
boost.test_adaboost()
elapsed = time.time() - starttime
#append values
training_acc.append(boost.training_accuracy)
testing_acc.append(boost.testing_accuracy)
list_tillnow.append(exampleno)
time_list.append(elapsed)
vid_utils.savefile(list_tillnow,training_acc,\
'data/training_acc_eg.txt')
vid_utils.savefile(list_tillnow,testing_acc,\
'data/testing_acc_eg.txt')
vid_utils.savefile(list_tillnow,time_list,\
'data/time_vals.txt')
plt.plot(exampleno_list, training_acc, 'bo-', label='Training Accuracy')
plt.plot(exampleno_list, testing_acc, 'ro-', label='Testing Accuracy')
plt.legend()
plt.show()
def training_round_script():
glob_const = globalconstants.GlobalConstants()
init_set(glob_const)
SNRval = 2.
#exampleno_list=[];
round_list = range(5, 30, 5)
training_acc = []
testing_acc = []
list_tillnow = []
time_list = []
pos_te_eg = glob_const.no_pos_testing_eg
neg_te_eg = glob_const.no_neg_testing_eg
for training_rounds in round_list:
starttime = time.time()
pos_training_eg = glob_const.no_pos_training_eg
neg_training_eg = glob_const.no_neg_training_eg
glob_const.savefile()
boost=adaboost_train_test.AdaBoostTrainTest(SNRval,training_rounds,\
pos_training_eg,neg_training_eg,pos_te_eg,neg_te_eg)
boost.train_adaboost()
boost.test_adaboost()
elapsed = time.time() - starttime
#append values
training_acc.append(boost.training_accuracy)
testing_acc.append(boost.testing_accuracy)
list_tillnow.append(training_rounds)
time_list.append(elapsed)
vid_utils.savefile(list_tillnow,training_acc,\
'data/training_acc_trainingrounds.txt')
vid_utils.savefile(list_tillnow,testing_acc,\
'data/testing_acc_trainingrounds.txt')
vid_utils.savefile(list_tillnow,time_list,\
'data/time_vals.txt')
plt.plot(round_list, training_acc, 'bo-', label='Training Accuracy')
plt.plot(round_list, testing_acc, 'ro-', label='Testing Accuracy')
plt.legend(loc=2)
plt.show()
def compare_script():
glob_const = globalconstants.GlobalConstants()
init_set(glob_const)
#SNRlist=[];
SNRlist = [0.25 * x for x in range(8, 9)]
tree_acc = []
boost_acc = []
training_rounds = 7
pos_tr_eg = glob_const.no_pos_training_eg
neg_tr_eg = glob_const.no_neg_training_eg
pos_te_eg = glob_const.no_pos_testing_eg
neg_te_eg = glob_const.no_neg_testing_eg
list_till_now = []
for SNRval in SNRlist:
boost=adaboost_train_test.AdaBoostTrainTest(SNRval,training_rounds,\
pos_tr_eg,neg_tr_eg,pos_te_eg,neg_te_eg)
traintest = train_and_test.TrainAndTest(SNRval)
#Train
boost.train_adaboost()
traintest.train_tree()
#Test
boost.test_adaboost()
traintest.test_tree()
#traintest.post_prune_tree();
#traintest.test_tree();
#get accuracies
boost_acc.append(boost.testing_accuracy)
tree_acc.append(traintest.testing_accuracy)
list_till_now.append(SNRval)
vid_utils.savefile(list_till_now, tree_acc, "data/Tree_accuracies.txt")
vid_utils.savefile(list_till_now, boost_acc,
"data/Boost_accuracies.txt")
print "Processed SNR: " + str(SNRval) + "..."
plt.plot(SNRlist, tree_acc, 'ro', label="Tree")
plt.plot(SNRlist, boost_acc, 'bo', label="Adaboost")
plt.xlim(0, 2.5)
plt.legend(loc=2)
plt.show()