SIENTIAPDE-1321: Added equation related methods

model_manager/utils/repository/training_repository.py

@@ -175,6 +175,10 @@ class TrainingRepository:
         )
 
         tmr.r2_val = round(r2(tmr.y_test.astype(np.float64), tmr.y_pred.astype(np.float64)), 2)
+        
+        # Extract model equation
+        tmr.equation = self._extract_model_equation(tmr.regr, params)
+        
         self.logger.info(
             f'Model metrics calculated successfully - experiment run id: {params.experiment_run_id}'
         )
@@ -249,3 +253,48 @@ class TrainingRepository:
             scaler_params={} if params.use_scaler else None,
             ar_var=params.target_variable if params.include_ar else None,
         )
+
+    def _extract_model_equation(self, regr: LinearRegressionModel, params: TrainModelParams) -> dict:
+        """
+        Extract the linear regression equation coefficients and create equation metadata.
+        
+        This method extracts the coefficients and intercept from the trained model
+        and creates a structured dictionary containing the equation information
+        for serialization as JSON artifact.
+        
+        Args:
+            regr: Trained LinearRegressionModel object
+            params: Training parameters containing variable information
+            
+        Returns:
+            dict: Equation metadata containing:
+                - target_variable: Name of the target variable
+                - coefficients: Dictionary mapping variable names to coefficients
+                - intercept: Model intercept value
+                - equation_string: Human-readable equation string
+                - latex_equation: LaTeX formatted equation
+        """
+        coefficients = regr.regr.coef_
+        intercept = regr.regr.intercept_
+        
+        # Create coefficients dictionary
+        coefficients_dict = {}
+        for i, var in enumerate(params.variable_columns):
+            coefficients_dict[var] = float(coefficients[i])
+        
+        # Create equation string
+        equation_parts = [f"{coef:.6f} * {var}" for var, coef in coefficients_dict.items()]
+        equation_string = f"{params.target_variable} = {intercept:.6f} + " + " + ".join(equation_parts)
+        
+        # Create LaTeX equation
+        latex_parts = [f"{coef:.6f} \\cdot {var}" for var, coef in coefficients_dict.items()]
+        latex_equation = f"{params.target_variable} = {intercept:.6f} + " + " + ".join(latex_parts)
+        
+        return {
+            'target_variable': params.target_variable,
+            'coefficients': coefficients_dict,
+            'intercept': float(intercept),
+            'equation_string': equation_string,
+            'latex_equation': latex_equation,
+            'model_type': 'Linear Regression'
+        }