def display_results_HBF1_task2():
##
# experiment = '/multiple_S_task2_HP_hbf2'
# path_to_experiments = './om_results_test_experiments'+experiment
# hbf1_multiple_experiment_results = get_results_for_experiments(path_to_experiments,verbose=True)
#mean_train_errors, std_train_errors, mean_test_errors_multiple, std_test_errors_multiple = get_error_stats(multiple_experiment_results)
path_to_experiments = './om_results_test_experiments/multiple_S_task2_HP_hbf2'
hbf1_multiple_experiment_results = get_results_for_experiments(
path_to_experiments, verbose=True)
#print hbf1_multiple_experiment_results
#
list_units, list_train_errors, list_test_errors = get_list_errors2(
experiment_results=hbf1_multiple_experiment_results)
#hbf1_list_units_single, hbf1_list_test_errors_single = get_list_errors(experiment_results=hbf1_single_experiment_results)
#
plt.figure(3)
print 'hbf1_list_units_multiple: ', list_units
print 'list_train_errors: ', list_train_errors
print 'list_test_errors: ', list_test_errors
krls.plot_errors(list_units,
list_train_errors,
label='HBF1 not shared HBF shape',
markersize=3,
colour='b')
krls.plot_errors(list_units,
list_test_errors,
label='HBF1 not shared HBF shape',
markersize=3,
colour='r')
plt.legend()
plt.show()
def display4D_2():
list_units = [5*5, 10*5, 15*5]
#list_units = 6*np.array([6,12,18])
nn1_list_test_errors = (8.971309392885537, 8.96969783241346, 8.971491006192313)
krls.plot_errors(list_units, nn1_list_test_errors,label='NN train error', markersize=3, colour='b')
#krls.plot_errors(list_units, nn1_list_test_errors,label='HBF1 test', markersize=3, colour='c')
bt_multiple_experiment_results = (8.96799373626709, 8.967977523803711, 8.968118667602539)
krls.plot_errors(list_units, bt_multiple_experiment_results,label='Binary Tree NN train error', markersize=3, colour='r')
plt.legend()
plt.show()
def display4D():
list_units = [5*5, 10*5, 15*5]
#list_units = 6*np.array([6,12,18])
nn_list_train_errors = [0.107502, 0.0313551, 0.00974167]
krls.plot_errors(list_units, nn_list_train_errors,label='NN train error', markersize=3, colour='b')
#krls.plot_errors(list_units, nn1_list_test_errors,label='HBF1 test', markersize=3, colour='c')
nn_list_train_errors = [0.047651, 0.012382, 0.008429]
krls.plot_errors(list_units, nn_list_train_errors,label='Binary Tree NN train error', markersize=3, colour='r')
plt.legend()
plt.show()
def display8D():
list_units = [7, 22, 45]
#list_units = 6*np.array([6,12,18])
nn1_list_test_errors = [0.951, 0.156, 0.0746]
krls.plot_errors(list_units, nn1_list_test_errors,label='NN test error', markersize=3, colour='b')
#krls.plot_errors(list_units, nn1_list_test_errors,label='HBF1 test', markersize=3, colour='c')
bt_multiple_experiment_results = [0.2495, 0.0668, 0.01066]
krls.plot_errors(list_units, bt_multiple_experiment_results,label='Binary Tree NN test error', markersize=3, colour='r')
plt.legend()
plt.show()
def display_results_multiple_vs_single():
##
experiment = '/multiple_S_dir'
path_to_experiments = './om_results_test_experiments' + experiment
multiple_experiment_results = get_results_for_experiments(
path_to_experiments)
mean_train_errors, std_train_errors, mean_test_errors_multiple, std_test_errors_multiple = get_error_stats(
multiple_experiment_results)
experiment = '/single_S_dir'
path_to_experiments = './om_results_test_experiments' + experiment
single_experiment_results = get_results_for_experiments(
path_to_experiments)
mean_train_errors, std_train_errors, mean_test_errors_single, std_test_errors_single = get_error_stats(
single_experiment_results)
print mean_test_errors_single
print std_test_errors_single
#
list_units_multiple, list_test_errors_multiple = get_list_errors(
experiment_results=multiple_experiment_results)
list_units_single, list_test_errors_single = get_list_errors(
experiment_results=single_experiment_results)
#
plt.figure(3)
krls.plot_errors(list_units_multiple,
list_test_errors_multiple,
label='HBF1 Multiple Standard Deviations',
markersize=3,
colour='r')
krls.plot_errors(list_units_single,
list_test_errors_single,
label='HBF1 Single Errors Standard Deviations',
markersize=3,
colour='b')
krls.plot_errors_and_bars(list_units_multiple,
mean_test_errors_multiple,
std_test_errors_multiple,
label='Multiple Errors',
markersize=3,
colour='b')
krls.plot_errors_and_bars(list_units_single,
mean_test_errors_single,
std_test_errors_single,
label='Single Errors',
markersize=3,
colour='r')
#
plt.legend()
plt.show()
def display_this():
get_k = lambda a: 7*a + 4*3*2*a**2
shallow = lambda k: 4*k+k+k
bt = lambda f: 2*f+f +2*f*(2*f)+ 2*(2*f)
nn1_list_test_errors = (0.024345317618429937, 0.003073343364860556, 0.0017753394536080345, 0.0011256201563784277, 0.009532295960287112, 0.007766131572159345)
bt_multiple_experiment_results = (0.0004508599522523582, 0.00015345749852713197, 1.3420359209703747e-05, 1.3420359209703747e-05, 1.3420359209703747e-05, 1.3420359209703747e-05)
#list_units = [ bt()]
list_units = [1,2, 3, 4, 5, 6]
krls.plot_errors(list_units, nn1_list_test_errors,label='NN train error', markersize=3, colour='b')
krls.plot_errors(list_units, bt_multiple_experiment_results,label='Binary Tree NN train error', markersize=3, colour='r')
plt.legend()
plt.show()
def display_results_HBF1_xsinglog1_x():
path_to_experiments = './om_results_test_experiments/task_27_july_NN1_depth_2_1000'
nn1_multiple_experiment_results = get_results_for_experiments(
path_to_experiments, verbose=True)
path_to_experiments = './om_results_test_experiments/task_27_july_NN2_depth_2_1000'
nn2_multiple_experiment_results = get_results_for_experiments(
path_to_experiments, verbose=True)
path_to_experiments = './om_results_test_experiments/task_27_july_NN3_depth_2_1000'
nn3_multiple_experiment_results = get_results_for_experiments(
path_to_experiments, verbose=True)
#
nn1_list_units, nn1_list_train_errors, nn1_list_test_errors = get_list_errors2(
experiment_results=nn1_multiple_experiment_results)
nn2_list_units, nn2_list_train_errors, nn2_list_test_errors = get_list_errors2(
experiment_results=nn2_multiple_experiment_results)
nn3_list_units, nn3_list_train_errors, nn3_list_test_errors = get_list_errors2(
experiment_results=nn3_multiple_experiment_results)
#
plt.figure(3)
#
list_units = np.array(nn1_list_units)
print list_units
krls.plot_errors(list_units,
nn1_list_train_errors,
label='NN1 train',
markersize=3,
colour='b')
krls.plot_errors(list_units,
nn1_list_test_errors,
label='NN1 test',
markersize=3,
colour='c')
#
list_units = 2 * np.array(nn2_list_units)
print list_units
krls.plot_errors(list_units,
nn2_list_train_errors,
label='NN2 train',
markersize=3,
colour='r')
krls.plot_errors(list_units,
nn2_list_test_errors,
label='NN2 test',
markersize=3,
colour='m')
#
list_units = 3 * np.array(nn3_list_units)
print list_units
krls.plot_errors(list_units,
nn3_list_train_errors,
label='NN3 train',
markersize=3,
colour='g')
krls.plot_errors(list_units,
nn3_list_test_errors,
label='NN3 test',
markersize=3,
colour='y')
plt.legend()
plt.show()
def display_results_HBF1_vs_HBF1():
##
experiment = '/multiple_S_dir'
path_to_experiments = './om_results_test_experiments' + experiment
hbf1_multiple_experiment_results = get_results_for_experiments(
path_to_experiments, verbose=True)
#mean_train_errors, std_train_errors, mean_test_errors_multiple, std_test_errors_multiple = get_error_stats(multiple_experiment_results)
experiment = '/single_S_dir'
path_to_experiments = './om_results_test_experiments' + experiment
hbf1_single_experiment_results = get_results_for_experiments(
path_to_experiments, verbose=True)
#mean_train_errors, std_train_errors, mean_test_errors_multiple, std_test_errors_multiple = get_error_stats(multiple_experiment_results)
experiment = '/hbf2_multiple_S'
path_to_experiments = './om_results_test_experiments' + experiment
hbf2_multiple_experiment_results = get_results_for_experiments(
path_to_experiments, verbose=True)
#mean_train_errors, std_train_errors, mean_test_errors_single, std_test_errors_single = get_error_stats(single_experiment_results)
experiment = '/hbf2_single_S'
path_to_experiments = './om_results_test_experiments' + experiment
hbf2_single_experiment_results = get_results_for_experiments(
path_to_experiments, verbose=True)
#mean_train_errors, std_train_errors, mean_test_errors_single, std_test_errors_single = get_error_stats(single_experiment_results)
#
hbf1_list_units_multiple, hbf1_list_test_errors_multiple = get_list_errors(
experiment_results=hbf1_multiple_experiment_results)
hbf1_list_units_single, hbf1_list_test_errors_single = get_list_errors(
experiment_results=hbf1_single_experiment_results)
hbf2_list_units_multiple, hbf2_list_test_errors_multiple = get_list_errors(
experiment_results=hbf2_multiple_experiment_results)
hbf2_list_units_single, hbf2_list_test_errors_single = get_list_errors(
experiment_results=hbf2_single_experiment_results)
#
plt.figure(3)
krls.plot_errors(hbf1_list_units_multiple,
hbf1_list_test_errors_multiple,
label='HBF1 Multiple Standard Deviations',
markersize=3,
colour='r')
krls.plot_errors(hbf1_list_units_multiple,
hbf1_list_test_errors_single,
label='HBF1 Single Errors Standard Deviations',
markersize=3,
colour='m')
print len(hbf2_list_test_errors_multiple)
print len(hbf1_list_units_multiple)
krls.plot_errors(2 * np.array(hbf2_list_units_multiple),
hbf2_list_test_errors_multiple,
label='HBF2 Multiple Standard Deviations',
markersize=3,
colour='b')
krls.plot_errors(2 * np.array(hbf2_list_units_multiple),
hbf2_list_test_errors_single,
label='HBF2 Single Errors Standard Deviations',
markersize=3,
colour='c')
#krls.plot_errors_and_bars(list_units_multiple, mean_test_errors_multiple, std_test_errors_multiple, label='Multiple Errors', markersize=3, colour='b')
#krls.plot_errors_and_bars(list_units_single, mean_test_errors_single, std_test_errors_single, label='Single Errors', markersize=3, colour='r')
#
plt.legend()
plt.show()