added griffins shit

src/griffin-stuff/backtester/main.py

@@ -0,0 +1,65 @@
+import json
+import logging
+import pandas as pd
+import os
+
+from indicators import calculate_indicator_signals
+from evaluation import evaluate_indicator_accuracy
+
+def setup_logging(log_path):
+    os.makedirs(os.path.dirname(log_path), exist_ok=True)
+    logging.basicConfig(
+        filename=log_path,
+        level=logging.INFO,
+        format='%(asctime)s - %(levelname)s - %(message)s'
+    )
+
+def load_config(config_path="config.json"):
+    with open(config_path, 'r') as f:
+        config = json.load(f)
+    return config
+
+def load_data(csv_path, date_col, price_col):
+    df = pd.read_csv(csv_path)
+    df[date_col] = pd.to_datetime(df[date_col])
+    df = df.sort_values(date_col).reset_index(drop=True)
+    df = df.dropna(subset=[date_col, price_col])
+    return df
+
+if __name__ == "__main__":
+    config = load_config("config.json")
+    setup_logging(config["evaluation"]["log_file"])
+    
+    # Load data
+    df = load_data(config["data"]["input_csv"], 
+                   config["data"]["date_column"], 
+                   config["data"]["price_column"])
+    
+    # Calculate indicators and signals, evaluate accuracy
+    all_results = []
+    for category, indicators in config["indicators"].items():
+        for ind_name in indicators:
+            params = config["parameters"].get(ind_name, {})
+            
+            signals_df = calculate_indicator_signals(
+                df.copy(),
+                indicator_name=ind_name,
+                params=params,
+                price_col=config["data"]["price_column"],
+                high_col=config["data"]["high_column"],
+                low_col=config["data"]["low_column"],
+                volume_col=config["data"]["volume_column"]
+            )
+            
+            accuracy = evaluate_indicator_accuracy(
+                signals_df, 
+                price_col=config["data"]["price_column"],
+                horizon=config["evaluation"]["prediction_horizon"]
+            )
+            
+            logging.info(f"Category: {category}, Indicator: {ind_name}, Accuracy: {accuracy:.4f}")
+            all_results.append((category, ind_name, accuracy))
+    
+    # Print results to console as well
+    for category, ind_name, acc in all_results:
+        print(f"Category: {category}, Indicator: {ind_name}, Accuracy: {acc:.4f}")