Go to the source code of this file.
Namespaces | |
| namespace | pr2_calibration_estimation::post_process |
Functions | |
| def | pr2_calibration_estimation::post_process::usage |
Variables | |
| tuple | pr2_calibration_estimation::post_process::all_sensor_types = list(set([x['sensor_type'] for x in all_sensors_dict.values()])) |
| tuple | pr2_calibration_estimation::post_process::all_sensors_dict = est_helpers.build_sensor_defs(sensors_dump) |
| tuple | pr2_calibration_estimation::post_process::bag = rosbag.Bag(bag_filename) |
| tuple | pr2_calibration_estimation::post_process::bag_filename = rospy.myargv() |
| list | pr2_calibration_estimation::post_process::bearing_list = [] |
| list | pr2_calibration_estimation::post_process::cam_covs = [matrix(array(s.compute_cov(fk)) * kron(eye(s.get_residual_length()/2),ones([2,2]))) for s,fk in zip(cam_sensors, fk_points)] |
| list | pr2_calibration_estimation::post_process::cam_Js = [s.compute_expected_J(fk) for s,fk in zip(cam_sensors, fk_points)] |
| list | pr2_calibration_estimation::post_process::cam_sensors = [[s for s in ms.sensors if s.sensor_id == cur_loop['cam']][0] for ms in multisensors_pruned] |
| list | pr2_calibration_estimation::post_process::cb_points = [SingleTransform(pose).transform * system_def.checkerboards[ms.checkerboard].generate_points() for pose, ms in zip(cb_poses_pruned,multisensors_pruned)] |
| tuple | pr2_calibration_estimation::post_process::cb_poses = yaml.load(open(output_dir + "/" + cur_step["output_filename"] + "_poses.yaml")) |
| list | pr2_calibration_estimation::post_process::chain_sensors = [[s for s in ms.sensors if s.sensor_id == cur_loop['3d']][0] for ms in multisensors_pruned] |
| tuple | pr2_calibration_estimation::post_process::circ_angles = numpy.linspace(0,2*numpy.pi, 360, endpoint=True) |
| tuple | pr2_calibration_estimation::post_process::circ_pos |
| tuple | pr2_calibration_estimation::post_process::config = rospy.get_param(config_param_name) |
| string | pr2_calibration_estimation::post_process::config_param_name = "calibration_config" |
| tuple | pr2_calibration_estimation::post_process::cur_scatter = plt.scatter(array(r)[:,0], array(r)[:,1], **cur_loop['plot_ops']) |
| list | pr2_calibration_estimation::post_process::cur_step = step_list[-1] |
| tuple | pr2_calibration_estimation::post_process::e = error_calc.calculate_error(opt_all_vec) |
| tuple | pr2_calibration_estimation::post_process::ellip = numpy.sqrt(4.6052) |
| tuple | pr2_calibration_estimation::post_process::ellip_shifted = array(ellip + r[k,:].T) |
| tuple | pr2_calibration_estimation::post_process::error_calc = opt_runner.ErrorCalc(system_def, free_dict, multisensors_pruned, False) |
| tuple | pr2_calibration_estimation::post_process::error_cat = numpy.concatenate(error_list) |
| tuple | pr2_calibration_estimation::post_process::errors_dict = opt_runner.compute_errors_breakdown(error_calc, multisensors_pruned, numpy.array(cb_poses_pruned)) |
| list | pr2_calibration_estimation::post_process::fk_covs = [matrix(array(s.compute_cov(None)) * kron(eye(s.get_residual_length()/3),ones([3,3]))) for s in chain_sensors] |
| list | pr2_calibration_estimation::post_process::fk_points = [s.get_measurement() for s in chain_sensors] |
| tuple | pr2_calibration_estimation::post_process::free_dict = yaml.load(cur_step["free_params"]) |
| list | pr2_calibration_estimation::post_process::full_covs = [matrix(cam_J)*fk_cov*matrix(cam_J).T + cam_cov for cam_J, cam_cov, fk_cov in zip(cam_Js, cam_covs, fk_covs)] |
| tuple | pr2_calibration_estimation::post_process::loop_list = yaml.load(open(loop_list_filename)) |
| tuple | pr2_calibration_estimation::post_process::loop_list_filename = rospy.myargv() |
| tuple | pr2_calibration_estimation::post_process::m = Marker() |
| int | pr2_calibration_estimation::post_process::marker_count = 0 |
| tuple | pr2_calibration_estimation::post_process::marker_fk_pub = rospy.Publisher("cal_markers", Marker) |
| tuple | pr2_calibration_estimation::post_process::marker_guess_pub = rospy.Publisher("cb_guess", Marker) |
| list | pr2_calibration_estimation::post_process::meas_points = [s.get_measurement() for s in cam_sensors] |
| tuple | pr2_calibration_estimation::post_process::ms = MultiSensor(sensor_defs) |
| list | pr2_calibration_estimation::post_process::multisensors = [] |
| tuple | pr2_calibration_estimation::post_process::opt_all_vec = opt_runner.build_opt_vector(system_def, free_dict, numpy.array(cb_poses_pruned)) |
| tuple | pr2_calibration_estimation::post_process::output_dir = rospy.myargv() |
| list | pr2_calibration_estimation::post_process::points_list_fk = [ geometry_msgs.msg.Point(cur_pt[0, 0], cur_pt[0, 1], cur_pt[0, 2]) for cur_pt in list(numpy.concatenate(fk_points,1).T)] |
| list | pr2_calibration_estimation::post_process::points_list_guess = [ geometry_msgs.msg.Point(cur_pt[0, 0], cur_pt[0, 1], cur_pt[0, 2]) for cur_pt in list(numpy.concatenate(cb_points,1).T)] |
| list | pr2_calibration_estimation::post_process::proj_points = [s.compute_expected(pts) for (s,pts) in zip(cam_sensors,fk_points)] |
| tuple | pr2_calibration_estimation::post_process::r = numpy.concatenate(proj_points) |
| tuple | pr2_calibration_estimation::post_process::rms_error = numpy.sqrt( numpy.mean(error_cat**2) ) |
| list | pr2_calibration_estimation::post_process::sample_ind = [k for k,ms in zip(range(len(multisensors)), multisensors) if len(ms.sensors) == 2] |
| list | pr2_calibration_estimation::post_process::scatter_list = [] |
| tuple | pr2_calibration_estimation::post_process::sensor_defs = est_helpers.load_requested_sensors(all_sensors_dict, [cur_loop['cam'], cur_loop['3d']]) |
| list | pr2_calibration_estimation::post_process::sensors_dump = [yaml.load(x) for x in config[sensors_name].values()] |
| string | pr2_calibration_estimation::post_process::sensors_name = "sensors" |
| tuple | pr2_calibration_estimation::post_process::step_list = est_helpers.load_calibration_steps(config["cal_steps"]) |
| tuple | pr2_calibration_estimation::post_process::system_def = RobotParams() |
| tuple | pr2_calibration_estimation::post_process::system_def_dict = yaml.load(open(output_dir + "/" + cur_step["output_filename"] + ".yaml")) |
