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) # 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)