Update README.md

README.md

@@ -43,23 +43,57 @@ To enable large-scale simulation with realistic temporal dynamics, SolarSys incl
 The project is organized into core modules and data folders.
 
 ```tree
-SolarSys/
-├── data/
-│   ├── per_house/              # Raw CSVs for diffusion model training
-│   ├── training/               # Cleaned RL training datasets
-│   └── testing/                # Cleaned RL evaluation datasets
-├── models/
-│   ├── diffusion_models/       # Trained Hierarchical Diffusion Model checkpoints
-│   ├── mappo_models/           # Trained MAPPO baselines and low-level agents
-│   └── inter_agent_models/     # Trained MeanField high-level coordinator
-├── Environment/
-│   ├── __init__.py
-│   └── solar_sys_environment.py # Custom Gym environment for flat RL
-├── cluster/
-│   ├── __init__.py
-│   └── inter_cluster_coordinator.py # Logic for high-level trade matching
-└── trainers/
-    ├── __init__.py
-    ├── hierarchical_train.py   # Main SolarSys HRL training script
-    └── evaluation_scripts/     # Scripts for baselines (PG, MADDPG, MAPPO, MFAC)
-
+SolarSys_Hugging_face/
+├── assets/                             
+├── requirements.txt                    # Project Dependencies
+├── Dataset/                            # Energy Data (Raw, Processed, and Synthetic)
+│   ├── Data/                           
+│   │   ├── Ausgrid_processed_data.zip  # Processed data (Australia)
+│   │   ├── Ausgrid_raw_data/
+│   │   └── Pecan_street_processed_data.zip # Processed data (US)
+│   └── Generated_Data.zip              # Example synthetic data (2000 agents)
+├── Data_generation_tool_kit/           # Hierarchical Diffusion Model Code
+│   ├── Hier_diffusion_energy/
+│   │   ├── hierarchial_diffusion_model.py # H-Diffusion U-Net Architecture
+│   │   └── global_scaler.gz            # Global normalization scaler, please delete and rerun if had problem
+│   ├── dataloader.py                   # 
+│   ├── train.py                        # Diffusion model training script
+│   └── generate.py                     # Script to generate long-term sequences
+├── Models/                             # Trained RL Policies for trial, please retrain your model for best results
+│   ├── 100agents_10size/
+│   │   └── models/
+│   │       ├── inter_ep10000.pth       # High-Level (Inter-Cluster) policy
+│   │       └── low_clusterX_ep10000.pth # Low-Level (Intra-Cluster) policies
+│   └── (Additional scaling folders)    # e.g., 5agents_5size/, 1000agents_20size/, etc.
+├── SolarSys/                           # SolarSys Implementation (MAPPO + MeanField)
+│   ├── Environment/
+│   │   ├── cluster_env_wrapper.py      # Vectorized environment wrapper
+│   │   └── solar_sys_environment.py    # Core Gym environment definition
+│   ├── mappo/                          # MAPPO policy definition (Intra-Cluster)
+│   │   └── trainer/
+│   │       └── mappo.py                # MAPPO algorithm
+│   ├── meanfield/                      # MeanField policy definition (Inter-Cluster)
+│   │   └── trainer/
+│   │       └── meanfield.py            # MeanField algorithm core
+│   ├── cluster.py                      # Inter-Cluster Coordinator logic
+│   ├── training_freezing.py            # Main SolarSys HRL training script
+│   └── cluster_evaluation.py           # Evaluation script for SolarSys
+└── Other_algorithms/                   # Baselines 
+    ├── HC_MAPPO/                       # Hierarchical Cluster MAPPO 
+    │   ├── Environment/
+    │   ├── HC_MAPPO_train.py           # Training script for HC-MAPPO
+    │   └── HC_MAPPO_evaluation.py      # Evaluation script for HC-MAPPO
+    └── Flat_System/                    # Flat Baselines 
+        ├── maddpg/                     # Multi-Agent DDPG
+        │   ├── maddpg_train.py
+        │   └── maddpg_evaluation.py
+        ├── mappo/                      # Flat MAPPO
+        │   ├── mappo_train.py
+        │   └── mappo_evaluation.py
+        ├── meanfield/                  # Flat MeanField Actor-Critic (MFAC)
+        │   ├── meanfield_train.py
+        │   └── meanfield_evaluation.py
+        ├── PG/                         # Policy Gradient (PG)
+        │   ├── pg_train.py
+        │   └── pg_evaluation.py
+        └── solar_sys_environment.py    # Copy of the flat environment for baselines