lint

sim/compare_h5.py

@@ -15,53 +15,56 @@
         
 """
 
+import argparse
 import h5py
 import numpy as np
 from pathlib import Path
-import argparse
+
 
 def load_h5_file(file_path):
     """Load H5 file and return a dictionary of datasets"""
     data = {}
-    with h5py.File(file_path, 'r') as f:
+    with h5py.File(file_path, "r") as f:
         # Recursively load all datasets
-        def load_group(group, prefix=''):
+        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
@@ -71,47 +74,45 @@ def compare_h5_files(issac_path, mujoco_path):
     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)
+
+        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')
-    
+    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)
-
 
+    compare_h5_files(args.isaac_file, args.mujoco_file)

sim/h5_logger.py

@@ -1,15 +1,23 @@
 """ Logger for logging data to HDF5 files """
 import os
 import uuid
+from datetime import datetime
 from typing import Dict
 
 import h5py
 import numpy as np
-from datetime import datetime
+import matplotlib.pyplot as plt  # dependency issues with python 3.8
 
 
 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
@@ -32,16 +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 = {
@@ -62,11 +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):
@@ -79,7 +93,7 @@ def close(self):
                 # Delete the file
                 os.remove(self.h5_file.filename)
                 return
-        
+
         self.h5_file.close()
 
     @staticmethod
@@ -116,7 +130,6 @@ def _plot_dataset(name: str, data: np.ndarray):
             name (str): Name of the dataset.
             data (np.ndarray): Data to be plotted.
         """
-        import matplotlib.pyplot as plt # dependency issues with python 3.8
         plt.figure(figsize=(10, 5))
         if data.ndim == 2:  # Handle multi-dimensional data
             for i in range(data.shape[1]):