Added simpler (provisional) information imbalance implementation

Author: diegodoimo

dadapy/metric_comparisons.py

@@ -73,6 +73,35 @@ def __init__(
             n_jobs=n_jobs,
         )
 
+    def return_information_imbalace(self, coordinates, k=1):
+
+        distances = None
+        dist_indices = None
+
+        assert any(
+            var is not None for var in [self.X, self.distances, self.dist_indices]
+        ), "MetricComparisons should be initialized with a dataset."
+
+        assert any(
+            var is not None for var in [coordinates, distances, dist_indices]
+        ), "The overlap with data requires a second dataset. \
+            Provide at least one of coordinates, distances, dist_indices."
+
+        dist_indices_base, _ = self._get_nn_indices(
+            self.X, self.distances, self.dist_indices, self.maxk
+        )
+
+        dist_indices_other, _ = self._get_nn_indices(
+            coordinates, distances, dist_indices, self.maxk
+        )
+
+        assert dist_indices_base.shape[0] == dist_indices_other.shape[0]
+
+        imb_ij = _return_imbalance(dist_indices_base, dist_indices_other, self.rng, k=k)
+        imb_ji = _return_imbalance(dist_indices_other, dist_indices_base, self.rng, k=k)
+
+        return imb_ij, imb_ji
+
     def return_inf_imb_two_selected_coords(self, coords1, coords2, k=1):
         """Return the imbalances between distances taken as the i and the j component of the coordinate matrix X.