def main():
input_path, output_path, dataset_name, symmetry_part_names = librr.parse_arguments(
input_path_postfix, output_path_root, output_dir_prefix)
instances = load_instances(input_path, output_path, -1)
filename = output_path + '/stats.csv'
print "Saving the file..."
print(filename)
file = open(filename, 'w')
num_attrs = len(attr_names)
assert(len(attr_types) == num_attrs)
for i in range(num_attrs):
if attr_types[i] == librr.AttrType.number:
all_attr_values = []
for instance in instances:
if not math.isnan(instance[i]):
all_attr_values.append(float(instance[i]))
mean_value = np.average(np.array(all_attr_values))
median_value = np.median(np.array(all_attr_values))
stdev_value = np.std(np.array(all_attr_values))
attr_name = attr_names[i].replace('_', ' ')
file.write(attr_name + ',')
file.write("{0:0.3f}".format(mean_value) + ',')
file.write("{0:0.3f}".format(median_value) + ',')
file.write("{0:0.3f}".format(stdev_value) + ',')
file.write('\n')
file.close()
'''
def main():
input_path, output_path, dataset_name, symmetry_part_names = librr.parse_arguments(
input_path_postfix, output_path_root, output_dir_prefix)
instances = load_instances(input_path, output_path, -1)
filename = output_path + '/stats.csv'
print "Saving the file..."
print(filename)
file = open(filename, 'w')
num_attrs = len(attr_names)
assert (len(attr_types) == num_attrs)
for i in range(num_attrs):
if attr_types[i] == librr.AttrType.number:
all_attr_values = []
for instance in instances:
if not math.isnan(instance[i]):
all_attr_values.append(float(instance[i]))
mean_value = np.average(np.array(all_attr_values))
median_value = np.median(np.array(all_attr_values))
stdev_value = np.std(np.array(all_attr_values))
attr_name = attr_names[i].replace('_', ' ')
file.write(attr_name + ',')
file.write("{0:0.3f}".format(mean_value) + ',')
file.write("{0:0.3f}".format(median_value) + ',')
file.write("{0:0.3f}".format(stdev_value) + ',')
file.write('\n')
file.close()
'''
def main():
input_path, output_path, dataset_name, symmetry_part_names = librr.parse_arguments(
input_path_postfix, output_path_root, output_dir_prefix)
data_dirname = os.path.basename(os.path.normpath(sys.argv[1]))
print(" >> " + data_dirname)
(all_accu_values, all_comp_values, x_values) = load_instances(input_path, output_path)
title = 'accu'
plt.plot(x_values, all_accu_values[0], label='Recon. Symmetry (Ours)')
plt.plot(x_values, all_accu_values[1], label='Recon. Database (Ours)')
plt.plot(x_values, all_accu_values[2], label='Recon. Fusion (Ours)')
plt.plot(x_values, all_accu_values[3], label='Part Assembly')
plt.plot(x_values, all_accu_values[4], label='Symmetry Detection')
plt.legend(loc=4)
plt.xlim(0, max_x_value)
plt.ylim(0, 1)
plt.xlabel('Neighbor Distance')
print(output_path_root + '/' + data_dirname + "_" + title)
plt.savefig(output_path_root + '/' + data_dirname + "_" + title)
plt.clf()
title = 'comp'
plt.plot(x_values, all_comp_values[0], label='Recon. Symmetry (Ours)')
plt.plot(x_values, all_comp_values[1], label='Recon. Database (Ours)')
plt.plot(x_values, all_comp_values[2], label='Recon. Fusion (Ours)')
plt.plot(x_values, all_comp_values[3], label='Part Assembly')
plt.plot(x_values, all_comp_values[4], label='Symmetry Detection')
plt.legend(loc=4)
plt.xlim(0, max_x_value)
plt.ylim(0, 1)
plt.xlabel('Neighbor Distance')
print(output_path_root + '/' + data_dirname + "_" + title)
plt.savefig(output_path_root + '/' + data_dirname + "_" + title)
def main():
input_path, output_path, dataset_name, symmetry_part_names = librr.parse_arguments(
input_path_postfix, output_path_root, output_dir_prefix)
instances = load_instances(input_path, output_path, -1)
html_filename = output_path + '/index.html'
librr.write_html_table(instances, attr_names, attr_types,
dataset_name + ' (All)', html_filename)
'''
def main():
input_path, output_path, dataset_name, symmetry_part_names = librr.parse_arguments(
input_path_postfix, output_path_root, output_dir_prefix)
instances = load_instances(input_path, output_path, -1)
html_filename = output_path + '/index.html'
librr.write_html_table(instances, attr_names, attr_types, dataset_name + ' (All)', html_filename)
'''
def main():
input_path, output_path, dataset_name, symmetry_part_names = librr.parse_arguments(
input_path_postfix, output_path_root, output_dir_prefix)
instances = load_instances(input_path, output_path, -1)
html_filename = output_path + '/index.html'
librr.write_html_table(instances, attr_names, attr_types, dataset_name + ' (All)', html_filename)
# For each part
for i in range(len(symmetry_part_names)):
instances = load_instances(input_path, output_path, i)
html_filename = output_path + '/' + symmetry_part_names[i] + '.html'
librr.write_html_table(instances, attr_names, attr_types,
dataset_name + ' (' + symmetry_part_names[i].title() + ')', html_filename)
def main():
input_path, output_path, dataset_name, symmetry_part_names = librr.parse_arguments(
input_path_postfix, output_path_root, output_dir_prefix)
load_instances(input_path, output_path, -1)