added a base class using the Abstract Class from python

BVAR/VARinfer.py

@@ -5,7 +5,7 @@
 import pytensor.tensor as at
 from .VARsim import VARSimulator
 from .utils import read_parameters
-from base_class.base_class import BaseModel
+from base_model.base_model import BaseModel
 
 
 class VARInfer(BaseModel):

base_model/__init__.py

@@ -0,0 +1 @@
+from .base_model import BaseModel

base_model/base_model.py

@@ -0,0 +1,87 @@
+from abc import ABC, abstractmethod
+import json
+import numpy as np
+from BVAR.VARsim import *
+from BVAR.VARinfer import *
+from gMLV.gMLV_sim import *
+from gMLV.gMLV_ML import *
+
+
+class BaseModel(ABC):
+    def __init__(self):
+        self.data = None
+        self.model = None
+        self.inference = None
+        self.parameters = None
+
+    @abstractmethod
+    def simulate(self, sim_type, *args, **kwargs):
+        if sim_type == "VAR":
+            return VARSimulator(*args, **kwargs)
+        elif sim_type == "gMLV":
+            return gMLV_sim(*args, **kwargs)
+        else:
+            raise ValueError("Unknown model type")
+
+    @abstractmethod
+    def infer(self, infer_type, *args, **kwargs):
+        if infer_type == "VAR":
+            return VARInfer(*args, **kwargs)
+        elif infer_type == "gMLV":
+            return gMLV_sim(*args, **kwargs)  # FIXME: change to gMLV_ML class
+        else:
+            raise ValueError("Unknown inference type")
+
+    @abstractmethod
+    def read_parameters(self, filepath):
+        """Read parameters from a JSON file."""
+        # Check if the filepath ends with .json
+        if not filepath.lower().endswith('.json'):
+            raise ValueError("Filepath must point to a .json file")
+
+        with open(filepath, 'r') as file:
+            parameters = json.load(file)
+            self.parameters = parameters
+
+    @abstractmethod
+    def save_parameters(self, filepath, parameters=None):
+        """Save parameters to a JSON file."""
+        if parameters is None:
+            parameters = self.parameters
+        if parameters is not None:
+            # Check if the filename ends with .json, if not append .json
+            if not filepath.endswith('.json'):
+                filepath += '.json'
+            with open(filepath, 'w') as file:
+                json.dump(parameters, file)
+        else:
+            print("No parameters to save.")
+
+    @abstractmethod
+    def print_parameters(self):
+        """Print parameters to the console."""
+        if self.parameters is not None:
+            print(json.dumps(self.parameters, indent=4))
+        else:
+            print("No parameters to print.")
+
+    @abstractmethod
+    def save_data(self, filename, data=None):
+        """Save data to a CSV file."""
+        if data is None:
+            data = self.data
+        if data is not None:
+            # Check if the filename ends with .csv, if not append .csv
+            if not filename.endswith('.csv'):
+                filename += '.csv'
+            np.savetxt(filename, data, delimiter=",")
+        else:
+            print("No data to save.")
+
+    @abstractmethod
+    def load_data(self, filename):
+        """Load data from a CSV file."""
+        file_extension = os.path.splitext(filename)[1]
+        if file_extension.lower() != ".csv":
+            raise ValueError("File is not a CSV file.")
+        self.data = np.loadtxt(filename, delimiter=",")