How to use the evo.tools.file_interface.read_tum_trajectory_file function in evo

def test_too_few_columns(self):
        self.mock_file.write(u"1 2 3 4 5 6 7")
        self.mock_file.seek(0)
        with self.assertRaises(file_interface.FileInterfaceException):
            file_interface.read_tum_trajectory_file(self.mock_file)

def test_too_few_columns_with_trailing_delim(self):
        self.mock_file.write(u"1 2 3 4 5 6 7 ")
        self.mock_file.seek(0)
        with self.assertRaises(file_interface.FileInterfaceException):
            file_interface.read_tum_trajectory_file(self.mock_file)

def test_trailing_delim(self):
        self.mock_file.write(u"0 0 0 0 0 0 0 1 ")
        self.mock_file.seek(0)
        with self.assertRaises(file_interface.FileInterfaceException):
            file_interface.read_tum_trajectory_file(self.mock_file)

def load_trajectories(args):
    import os
    from collections import OrderedDict
    from evo.tools import file_interface
    trajectories = OrderedDict()
    ref_traj = None
    if args.subcommand == "tum":
        for traj_file in args.traj_files:
            if traj_file == args.ref:
                continue
            trajectories[traj_file] = file_interface.read_tum_trajectory_file(
                traj_file)
        if args.ref:
            ref_traj = file_interface.read_tum_trajectory_file(args.ref)
    elif args.subcommand == "kitti":
        for pose_file in args.pose_files:
            if pose_file == args.ref:
                continue
            trajectories[pose_file] = file_interface.read_kitti_poses_file(
                pose_file)
        if args.ref:
            ref_traj = file_interface.read_kitti_poses_file(args.ref)
    elif args.subcommand == "euroc":
        for csv_file in args.state_gt_csv:
            if csv_file == args.ref:
                continue
            else:

def load_trajectories(args):
    import os
    from collections import OrderedDict
    from evo.tools import file_interface
    trajectories = OrderedDict()
    ref_traj = None
    if args.subcommand == "tum":
        for traj_file in args.traj_files:
            if traj_file == args.ref:
                continue
            trajectories[traj_file] = file_interface.read_tum_trajectory_file(
                traj_file)
        if args.ref:
            ref_traj = file_interface.read_tum_trajectory_file(args.ref)
    elif args.subcommand == "kitti":
        for pose_file in args.pose_files:
            if pose_file == args.ref:
                continue
            trajectories[pose_file] = file_interface.read_kitti_poses_file(
                pose_file)
        if args.ref:
            ref_traj = file_interface.read_kitti_poses_file(args.ref)
    elif args.subcommand == "euroc":
        for csv_file in args.state_gt_csv:
            if csv_file == args.ref:
                continue
            else:
                trajectories[
                    csv_file] = file_interface.read_euroc_csv_trajectory(
                        csv_file)

#!/usr/bin/env python

from __future__ import print_function

print("loading required evo modules")
from evo.core import trajectory, sync, metrics
from evo.tools import file_interface

print("loading trajectories")
traj_ref = file_interface.read_tum_trajectory_file(
    "../../test/data/fr2_desk_groundtruth.txt")
traj_est = file_interface.read_tum_trajectory_file(
    "../../test/data/fr2_desk_ORB.txt")

print("registering and aligning trajectories")
traj_ref, traj_est = sync.associate_trajectories(traj_ref, traj_est)
traj_est = trajectory.align_trajectory(traj_est, traj_ref, correct_scale=False)

print("calculating APE")
data = (traj_ref, traj_est)
ape_metric = metrics.APE(metrics.PoseRelation.translation_part)
ape_metric.process_data(data)
ape_statistics = ape_metric.get_all_statistics()
print("mean:", ape_statistics["mean"])

print("loading plot modules")

def load_trajectories(args):
    from evo.core import sync
    from evo.tools import file_interface

    if args.subcommand == "tum":
        traj_ref = file_interface.read_tum_trajectory_file(args.ref_file)
        traj_est = file_interface.read_tum_trajectory_file(args.est_file)
        ref_name, est_name = args.ref_file, args.est_file
    elif args.subcommand == "kitti":
        traj_ref = file_interface.read_kitti_poses_file(args.ref_file)
        traj_est = file_interface.read_kitti_poses_file(args.est_file)
        ref_name, est_name = args.ref_file, args.est_file
    elif args.subcommand == "euroc":
        traj_ref = file_interface.read_euroc_csv_trajectory(args.state_gt_csv)
        traj_est = file_interface.read_tum_trajectory_file(args.est_file)
        ref_name, est_name = args.state_gt_csv, args.est_file
    elif args.subcommand == "bag":
        import os
        logger.debug("Opening bag file " + args.bag)
        if not os.path.exists(args.bag):
            raise file_interface.FileInterfaceException(
                "File doesn't exist: {}".format(args.bag))
        import rosbag

#!/usr/bin/env python

from __future__ import print_function

print("loading required evo modules")
from evo.core import trajectory, sync, metrics
from evo.tools import file_interface

print("loading trajectories")
traj_ref = file_interface.read_tum_trajectory_file(
    "../../test/data/fr2_desk_groundtruth.txt")
traj_est = file_interface.read_tum_trajectory_file(
    "../../test/data/fr2_desk_ORB.txt")

print("registering and aligning trajectories")
traj_ref, traj_est = sync.associate_trajectories(traj_ref, traj_est)
traj_est = trajectory.align_trajectory(traj_est, traj_ref, correct_scale=False)

print("calculating APE")
data = (traj_ref, traj_est)
ape_metric = metrics.APE(metrics.PoseRelation.translation_part)
ape_metric.process_data(data)
ape_statistics = ape_metric.get_all_statistics()
print("mean:", ape_statistics["mean"])

print("loading plot modules")
from evo.tools import plot
import matplotlib.pyplot as plt