Add logging for h5

sim/compare_h5.py

@@ -0,0 +1,119 @@
+"""
+Compare two HDF5 files and analyze their differences.
+
+Usage:
+    python compare_h5.py --isaac-file path/to/isaac.h5 --mujoco-file path/to/mujoco.h5
+
+Example:
+    python sim/compare_h5.py \
+        --isaac-file runs/h5_out/stompypro/2024-12-02_20-04-51/env_0/stompypro_env_0/h5_out/2024-12-02_20-04-51__053b2b5b-21c9-497c-b637-b66935dfe475.h5 \
+        --mujoco-file sim/resources/stompypro/h5_out/2024-12-02_21-10-41__5820ade7-9fc0-46df-8469-2f305480bcae.h5
+
+    python sim/compare_h5.py \
+        --isaac-file runs/h5_out/stompypro/2024-12-02_20-04-51/env_1/stompypro_env_1/h5_out/2024-12-02_20-04-51__d2016a6f-a486-4e86-8c5e-c9addd2cc13e.h5 \
+        --mujoco-file sim/resources/stompypro/h5_out/2024-12-02_21-10-41__5820ade7-9fc0-46df-8469-2f305480bcae.h5
+
+"""
+
+import argparse
+from pathlib import Path
+
+import h5py
+import numpy as np
+
+
+def load_h5_file(file_path):
+    """Load H5 file and return a dictionary of datasets"""
+    data = {}
+    with h5py.File(file_path, "r") as f:
+        # Recursively load all datasets
+        def load_group(group, prefix=""):
+            for key in group.keys():
+                path = f"{prefix}/{key}" if prefix else key
+                if isinstance(group[key], h5py.Group):
+                    load_group(group[key], path)
+                else:
+                    data[path] = group[key][:]
+
+        load_group(f)
+    return data
+
+
+def compare_h5_files(issac_path, mujoco_path):
+    """Compare two H5 files and print differences"""
+    print(f"\nLoading files:")
+    print(f"Isaac: {issac_path}")
+    print(f"Mujoco: {mujoco_path}")
+
+    # Load both files
+    issac_data = load_h5_file(issac_path)
+    mujoco_data = load_h5_file(mujoco_path)
+
+    print("\nFile lengths:")
+    print(f"Isaac datasets: {len(issac_data)}")
+    print(f"Mujoco datasets: {len(mujoco_data)}")
+
+    print("\nDataset shapes:")
+    print("\nIsaac shapes:")
+    for key, value in issac_data.items():
+        print(f"{key}: {value.shape}")
+
+    print("\nMujoco shapes:")
+    for key, value in mujoco_data.items():
+        print(f"{key}: {value.shape}")
+
+    # Find common keys
+    common_keys = set(issac_data.keys()) & set(mujoco_data.keys())
+    print(f"\nCommon datasets: {len(common_keys)}")
+
+    # Find uncommon keys
+    issac_only_keys = set(issac_data.keys()) - common_keys
+    mujoco_only_keys = set(mujoco_data.keys()) - common_keys
+    print(f"\nIsaac only datasets: {len(issac_only_keys)}")
+    for key in issac_only_keys:
+        print(f"Isaac only: {key}")
+    print(f"\nMujoco only datasets: {len(mujoco_only_keys)}")
+    for key in mujoco_only_keys:
+        print(f"Mujoco only: {key}")
+
+    # Compare data for common keys
+    for key in common_keys:
+        issac_arr = issac_data[key]
+        mujoco_arr = mujoco_data[key]
+
+        print(f"\n========== For {key} ===============")
+
+        if issac_arr.shape != mujoco_arr.shape:
+            print(f"\n{key} - Shape mismatch: Isaac {issac_arr.shape} vs Mujoco {mujoco_arr.shape}")
+
+        # Calculate differences
+        min_shape = min(issac_arr.shape[0], mujoco_arr.shape[0])
+        if issac_arr.shape != mujoco_arr.shape:
+            raise ValueError(f"Shapes do not match for {key}. Cannot compare datasets with different shapes.")
+        diff = np.abs(issac_arr[:min_shape] - mujoco_arr[:min_shape])
+        max_diff = np.max(diff)
+        mean_diff = np.mean(diff)
+
+        print(f"Max difference: {max_diff:.6f}")
+        print(f"Mean difference: {mean_diff:.6f}\n")
+
+        start_idx = 0
+        display_timesteps = 10
+        end_idx = start_idx + display_timesteps
+
+        np.set_printoptions(formatter={"float": "{:0.6f}".format}, suppress=True)
+        print("Isaac:\n", issac_arr[start_idx:end_idx])
+        print("Mujoco:\n", mujoco_arr[start_idx:end_idx])
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Compare two H5 files from Isaac and Mujoco simulations")
+    parser.add_argument("--isaac-file", required=True, help="Path to Isaac simulation H5 file")
+    parser.add_argument("--mujoco-file", required=True, help="Path to Mujoco simulation H5 file")
+
+    args = parser.parse_args()
+
+    print(f"Isaac path: {args.isaac_file}")
+    print(f"Mujoco path: {args.mujoco_file}")
+
+    compare_h5_files(args.isaac_file, args.mujoco_file)

sim/h5_logger.py

@@ -1,16 +1,23 @@
 """ Logger for logging data to HDF5 files """
 import os
 import uuid
+from datetime import datetime
 from typing import Dict
 
 import h5py
-import matplotlib.pyplot as plt
+import matplotlib.pyplot as plt  # dependency issues with python 3.8
 import numpy as np
-from datetime import datetime
 
 
 class HDF5Logger:
-    def __init__(self, data_name: str, num_actions: int, max_timesteps: int, num_observations: int, h5_out_dir: str = "sim/resources/"):
+    def __init__(
+        self,
+        data_name: str,
+        num_actions: int,
+        max_timesteps: int,
+        num_observations: int,
+        h5_out_dir: str = "sim/resources/",
+    ):
         self.data_name = data_name
         self.num_actions = num_actions
         self.max_timesteps = max_timesteps
@@ -33,16 +40,22 @@ def _create_h5_file(self):
         h5_file = h5py.File(h5_file_path, "w")
 
         # Create datasets for logging actions and observations
-        dset_prev_actions = h5_file.create_dataset("prev_actions", (self.max_timesteps, self.num_actions), dtype=np.float32)
+        dset_prev_actions = h5_file.create_dataset(
+            "prev_actions", (self.max_timesteps, self.num_actions), dtype=np.float32
+        )
         dset_2D_command = h5_file.create_dataset("observations/2D_command", (self.max_timesteps, 2), dtype=np.float32)
         dset_3D_command = h5_file.create_dataset("observations/3D_command", (self.max_timesteps, 3), dtype=np.float32)
         dset_q = h5_file.create_dataset("observations/q", (self.max_timesteps, self.num_actions), dtype=np.float32)
         dset_dq = h5_file.create_dataset("observations/dq", (self.max_timesteps, self.num_actions), dtype=np.float32)
         dset_ang_vel = h5_file.create_dataset("observations/ang_vel", (self.max_timesteps, 3), dtype=np.float32)
         dset_euler = h5_file.create_dataset("observations/euler", (self.max_timesteps, 3), dtype=np.float32)
         dset_t = h5_file.create_dataset("observations/t", (self.max_timesteps, 1), dtype=np.float32)
-        dset_buffer = h5_file.create_dataset("observations/buffer", (self.max_timesteps, self.num_observations), dtype=np.float32)
-        dset_curr_actions = h5_file.create_dataset("curr_actions", (self.max_timesteps, self.num_actions), dtype=np.float32)
+        dset_buffer = h5_file.create_dataset(
+            "observations/buffer", (self.max_timesteps, self.num_observations), dtype=np.float32
+        )
+        dset_curr_actions = h5_file.create_dataset(
+            "curr_actions", (self.max_timesteps, self.num_actions), dtype=np.float32
+        )
 
         # Map datasets for easy access
         h5_dict = {
@@ -63,11 +76,11 @@ def log_data(self, data: Dict[str, np.ndarray]):
         if self.current_timestep >= self.max_timesteps:
             print(f"Warning: Exceeded maximum timesteps ({self.max_timesteps})")
             return
-            
+
         for key, dataset in self.h5_dict.items():
             if key in data:
                 dataset[self.current_timestep] = data[key]
-        
+
         self.current_timestep += 1
 
     def close(self):
@@ -80,7 +93,7 @@ def close(self):
                 # Delete the file
                 os.remove(self.h5_file.filename)
                 return
-        
+
         self.h5_file.close()
 
     @staticmethod