Grouped the results of construction tasks by materials and rooms. Displayed using prettytable

analyze_construction_tasks.py

@@ -1,39 +1,89 @@
-import boto3
 import os
 import json
+from collections import defaultdict
+from prettytable import PrettyTable
 import re
-from botocore.exceptions import ClientError
-import json
-import argparse
-from tqdm import tqdm
-import glob
 
+def extract_success_scores(root_dir):
+    task_scores = {}  # Stores task-wise scores
+    material_groups = defaultdict(list)
+    room_groups = defaultdict(list)
     
-def analyze_json_file(file_path):
+    # Regex pattern to extract material and room numbers
-    """
+    pattern = re.compile(r"materials_(\d+)_rooms_(\d+)")
-    Analyzes a single JSON file to extract the task outcome.
 
-    Args:
+    # Iterate through each task folder
-        file_path (str): Path to the JSON file.
+    for task_folder in os.listdir(root_dir):
+        task_path = os.path.join(root_dir, task_folder)
+        if os.path.isdir(task_path):
+            logs_found = False  # Flag to track if logs exist
             
-    Returns:
+            # Check for JSON files
-        str or None: The task outcome string if found, otherwise None.
+            for file_name in os.listdir(task_path):
-    """
+                if file_name.endswith(".json"): 
+                    logs_found = True  # JSON file exists
+                    file_path = os.path.join(task_path, file_name)
+                    
+                    # Read JSON file
                     try:
-        with open(file_path, 'r') as f:
+                        with open(file_path, 'r') as file:
-            data = json.load(f)
+                            data = json.load(file)
-            if 'turns' in data and isinstance(data['turns'], list):
+                            
-                for turn in reversed(data['turns']):  # Check turns from the end
+                            # Extract success score from the last system message
-                    if turn.get('role') == 'system' and isinstance(turn.get('content'), str):
+                            for turn in reversed(data.get("turns", [])):
-                        if "Task successful ended with code : 2" in turn['content'] or "Task ended in score: 1" in turn["content"]:
+                                if turn["role"] == "system" and "Task ended with score" in turn["content"]:
-                            return True
+                                    score = float(turn["content"].split(":")[-1].strip())
-        return False
+                                    task_scores[task_folder] = score  # Store per-task score
-    except FileNotFoundError:
+                                    break  # Stop searching if found
-        print(f"Error: File not found: {file_path}")
+                            
-        return None
+                            # Stop checking other files in the folder if score is found
-    except json.JSONDecodeError:
+                            if task_folder in task_scores:
-        print(f"Error: Invalid JSON format in: {file_path}")
+                                break 
-        return None
                     except Exception as e:
-        print(f"An unexpected error occurred while processing {file_path}: {e}")
+                        print(f"Error reading {file_path}: {e}")
-        return None
+            
+            # If no logs were found, print a message
+            if not logs_found:
+                print(f"No log files found in {task_folder}")
+
+    # Group scores by material and room
+    for task, score in task_scores.items():
+        match = pattern.search(task)
+        if match:
+            material = int(match.group(1))  # Extract material number
+            room = int(match.group(2))  # Extract room number
+            material_groups[material].append(score)
+            room_groups[room].append(score)
+        else:
+            print(f"Warning: Task folder '{task}' does not match expected format.")
+
+    # Calculate average scores
+    def calculate_average(group):
+        return {key: sum(values) / len(values) for key, values in group.items()}
+
+    avg_material_scores = calculate_average(material_groups)
+    avg_room_scores = calculate_average(room_groups)
+
+    # Display results using PrettyTable
+    def display_table(title, data):
+        table = PrettyTable(["Category", "Average Score"])
+        for key, value in sorted(data.items()):
+            table.add_row([key, round(value, 2)])
+        print(f"\n{title}")
+        print(table)
+
+    def display_task_scores():
+        table = PrettyTable(["Task", "Success Score"])
+        for task, score in sorted(task_scores.items()):
+            table.add_row([task, round(score, 2)])
+        print("\nTask-wise Success Scores")
+        print(table)
+
+    # Print all tables
+    display_task_scores()
+    display_table("Average Success Score by Material (Grouped by Number)", avg_material_scores)
+    display_table("Average Success Score by Room (Grouped by Number)", avg_room_scores)
+
+# Example usage (replace 'root_directory' with actual path)
+root_directory = "experiments/exp_03-22_19-29"
+extract_success_scores(root_directory)