From cff42131da32bb73f229bc903033b715b9f0338c Mon Sep 17 00:00:00 2001
From: Hiyeri <48970646+Hiyeri@users.noreply.github.com>
Date: Thu, 13 Oct 2022 13:15:35 +0200
Subject: [PATCH] add multivar seed_target_indices

---
 mne_connectivity/utils/utils.py | 34 +++++++++++++++++++++++++++++++++
 1 file changed, 34 insertions(+)

diff --git a/mne_connectivity/utils/utils.py b/mne_connectivity/utils/utils.py
index 5ae94acb..ba8af393 100644
--- a/mne_connectivity/utils/utils.py
+++ b/mne_connectivity/utils/utils.py
@@ -98,6 +98,40 @@ def seed_target_indices(seeds, targets):
 
     return indices
 
+def multivar_seed_target_indices(
+    seeds: ArrayLike, targets: ArrayLike
+) -> tuple[ArrayLike]:
+    """Generates indices parameter for seed-based multivariate connectivity
+    analysis.
+    PARAMETERS
+    ----------
+    seeds : array of array of int
+    -   Seed indices, consisting of an array composed of sub-arrays, where each
+        each sub-array contains the indices of the channels for the seeds of a
+        single connectivity node.
+    targets : array of array of int
+    -   Target indices, consisting of an array composed of sub-arrays, where
+        each each sub-array contains the indices of the channels for the targets
+        of a single connectivity node. For each "seeds" sub-array, a
+        corresponding entry for each of the "targets" sub-arrays will be added
+        to the indices.
+    RETURNS
+    -------
+    indices : tuple of array of array of int
+    -   The indices paramater used for multivariate connectivity computation.
+        Consists of two arrays corresponding to the seeds and targets,
+        respectively, where each array is composed of sub-arrays, where each
+        sub-array contains the indices of the channels for the seeds/targets of
+        a single connectivity node.
+    """
+    indices = [[], []]
+    for seed in seeds:
+        for target in targets:
+            indices[0].append(seed)
+            indices[1].append(target)
+
+    return tuple(indices)
+
 
 def degree(connectivity, threshold_prop=0.2):
     """Compute the undirected degree of a connectivity matrix.