def plot_aggregate_figure_for_hetero_performance(parsed_data_hetero):
prr_by_config_list, spurious_by_config_list, stds_prr, stds_spurious = \
Parser.get_avg_perfect_recall_and_avg_spurious_recall_from_data_for_configs(
parsed_data_hetero, iterations_per_config=20, num_of_configs=2)
plt.rcParams.update({'font.size': 25})
plt.title('Average number of recalled patterns by subset')
# Plotting:
width = .35
x = np.asarray([2, 3, 4, 5])
plt.rcParams.update({'font.size': 25})
print prr_by_config_list[0]
print prr_by_config_list[1]
for list_ctr in range(len(prr_by_config_list)):
for el_ctr in range(len(prr_by_config_list[0])):
prr_by_config_list[list_ctr][el_ctr] *= (el_ctr+2)
spurious_by_config_list[list_ctr][el_ctr] *= (el_ctr+2)
# print "prr[0]:", prr_by_config_list[0]
p1 = plt.bar(x, prr_by_config_list[0], color='y', width= width)
p1_e = plt.bar(x, spurious_by_config_list[0], color='r', width=width, bottom=prr_by_config_list[0])
p2 = plt.bar(x + width, prr_by_config_list[1], color='g', width=width)
p2_2 = plt.bar(x + width, spurious_by_config_list[1], color='r', width=width,
bottom=prr_by_config_list[1])
plt.ylabel('Average number of recalled patterns')
plt.xlabel('Subset size')
plt.xticks(x + width, ('2x5', '3x5', '4x5', '5x5'))
# plt.yticks(np.arange(0, 6, 1))
plt.legend((p1[0], p2[0], p2_2),
('Perfectly recalled patterns, '+r'$\tau=0.30$',
'Perfectly recalled patterns, '+r'$\tau=0.50$',
'Spuriously recalled patterns'), bbox_to_anchor=(0.73, 1.0), ncol=1, fancybox=True, shadow=True)
# p2 = plt.plot(results_2[0], res
# plt.legend((p2[0], p3[0], p4[0], p5[0]), ('2x5', '3x5', '4x5', '5x5'),
# bbox_to_anchor=(1.115, 1.0155), ncol=1, fancybox=True, shadow=True)
plt.margins(0.02)
plt.subplots_adjust(left=0.06)
plt.grid(True)
def process_3d_data(current_data, iterations_per_config, num_of_configs):
prr_by_config_list, spurious_by_config_list, stds_prr, stds_spurious = \
Parser.get_avg_perfect_recall_and_avg_spurious_recall_from_data_for_configs(
current_data, iterations_per_config=iterations_per_config, num_of_configs=num_of_configs)
# print "spurious_by_dgw_list:", spurious_by_dgw_list
values_prrs = []
values_spurious = []
config_ctr = 0
for avg_list in prr_by_config_list:
x_ctr = 2
for avg_val in avg_list:
x = x_ctr - _x_width/2.
y = config_ctr
z = avg_val
values_prrs.append([x, y, z])
x_ctr += 1
config_ctr += 1
config_ctr = 0
for avg_list in spurious_by_config_list:
x_ctr = 2
for avg_val in avg_list:
x = x_ctr - _x_width/2.
y = config_ctr
z = avg_val
values_spurious.append([x, y, z])
x_ctr += 1
config_ctr += 1
return [values_prrs, values_spurious]
