test to load the traces from thomas W.

Unfortunately, 6DoF and not 5Dof

Also did a small snippet in example/ to create a video from hdf5

.gitignore

@@ -6,6 +6,7 @@ __pycache__/
 
 # C extensions
 *.so
+*.hdf5
 
 # Distribution / packaging
 .Python

examples/trace_hdf5_img.py

@@ -0,0 +1,28 @@
+
+import h5py, tqdm
+import matplotlib.pyplot as plt
+import matplotlib.cm as cm
+import matplotlib.animation as animation
+
+
+# Specify the path to your HDF5 file
+file_path = 'data/episode_46.hdf5'
+
+# Open the HDF5 file
+with h5py.File(file_path, 'r') as file:
+
+    # Access the datasets or attributes in the file
+    # For example, to access a dataset named 'data':
+    group_obs_img = file['observations/images/front']
+
+    img = [] # some array of images
+    frames = [] # for storing the generated images
+
+    # Write each image to the video
+    fig = plt.figure()
+    for i in tqdm.tqdm(range(group_obs_img.shape[0]), desc='Writing video'):
+        frames.append([plt.imshow(group_obs_img[i],animated=True)])
+
+    ani = animation.ArtistAnimation(fig, frames, interval=50, blit=True,
+                                    repeat_delay=1000)
+    ani.save('movie.mp4')

examples/trace_hdf5_mujoco.py

@@ -0,0 +1,46 @@
+import h5py
+import time
+
+import mujoco
+import mujoco.viewer
+import numpy as np
+
+from gym_lowcostrobot.simulated_robot import SimulatedRobot
+
+def do_replay_hdf5():
+
+    # Specify the path to your HDF5 file
+    file_path = 'data/episode_46.hdf5'
+    with h5py.File(file_path, 'r') as file:
+
+        m = mujoco.MjModel.from_xml_path("assets/scene_one_cube.xml")
+        data = mujoco.MjData(m)
+        robot = SimulatedRobot(m, data)
+
+        group_action = file['action']
+        group_qpos = file['observations/qpos']
+
+        with mujoco.viewer.launch_passive(m, data) as viewer:
+
+            # Run the simulation
+            step = 0
+            while viewer.is_running():
+                step_start = time.time()
+
+                # Step the simulation forward
+                robot.set_target_pos(group_action[step][0:5])
+                mujoco.mj_step(m, data)
+
+                viewer.sync()
+
+                # Rudimentary time keeping, will drift relative to wall clock.
+                time_until_next_step = m.opt.timestep - (time.time() - step_start)
+                if time_until_next_step > 0:
+                    time.sleep(time_until_next_step)
+
+                step += 1
+                step = step % len(group_qpos)
+
+
+if __name__ == "__main__":
+    do_replay_hdf5()