feat(agora.utils): add lineage grouping function

src/agora/utils/lineage.py

 #!/usr/bin/env python3
+import re
+import typing as t
+
 import numpy as np
 import pandas as pd
 
 from agora.io.bridge import groupsort
+from itertools import groupby
 
 
 def mb_array_to_dict(mb_array: np.ndarray):
@@ -25,3 +29,51 @@ def mb_array_to_indices(mb_array: np.ndarray):
     return pd.MultiIndex.from_arrays(mb_array[:, :2].T).union(
         pd.MultiIndex.from_arrays(mb_array[:, [0, 2]].T)
     )
+
+
+def group_matrix(
+    matrix: np.ndarray,
+    n_keys: int = 2,
+) -> t.Dict[t.Tuple[int], t.List[int]]:
+    """Group a matrix of integers by grouping the first two columns
+    and setting the third one in a list.
+
+
+    Parameters
+    ----------
+    matrix : np.ndarray
+        id_matrix, generally its columns are three integers indicating trap,
+        mother and daughter.
+    n_keys : int
+        number of keys to use to determine groups.
+
+    Returns
+    -------
+    t.Dict[t.Tuple[int], t.Collection[int, ...]]
+        The column(s) not used for generaeting keys are grouped as values.
+
+    Examples
+    --------
+    FIXME: Add docs.
+
+    """
+    lineage_dict = {}
+    if len(matrix):
+
+        daughter = matrix[:, n_keys]
+        mother_global_id = matrix[:, :n_keys]
+
+        iterator = groupby(
+            zip(mother_global_id, daughter), lambda x: str(x[0])
+        )
+        lineage_dict = {key: [x[1] for x in group] for key, group in iterator}
+
+        def str_to_tuple(k: str) -> t.Tuple[int, ...]:
+            return tuple([int(x) for x in re.findall("[0-9]+", k)])
+
+        # Convert keys from str to tuple
+        lineage_dict = {
+            str_to_tuple(k): sorted(v) for k, v in lineage_dict.items()
+        }
+
+    return lineage_dict