Created base structure for adding discovery and other algorithms

pywhyllm/datasets/dataset.py

@@ -0,0 +1,33 @@
+from typing import List, Protocol
+
+class Dataset(Protocol):
+
+    def graph(self):
+        """
+        Output the graph associated with the dataset. 
+
+        Args:
+        Returns:
+            A networkx graph 
+        """
+        pass
+
+    def data(self):
+        """
+        Output the data associated with the dataset.
+
+        Args:
+        Returns:
+            A numpy array containing the data
+        """
+        pass
+
+    def generate_data(self):
+        """
+        Generate synthetic data based on the dataset's causal graph.
+
+        Args:
+        Returns:
+            A numpy array containing the synthetic data
+        """
+        pass

pywhyllm/datasets/metrics.py

@@ -0,0 +1,25 @@
+
+
+def accuracy(edges, true_edges):
+    """Accuracy metric for predicted edges
+    """
+    pass
+
+
+def precision(edges, true_edges):
+    """Precision metric for predicted edges
+    """
+    pass
+
+
+def recall(edges, true_edges):
+    """Recall metric for predicted edges
+    """
+    pass
+
+
+def F1(edges, true_edges)
+    """F1 metric for predicted edges
+    """
+    pass
+