Pairwise distance metric keyword for stats.isc (#442)

* added similarity metric keyword to stats.isc (defaults to correlation)

* add description for sim_metric

* Update stats.py

nltools/stats.py

@@ -1943,6 +1943,7 @@ def isc(
     tail=2,
     n_jobs=-1,
     random_state=None,
+    sim_metric="correlation",
 ):
     """Compute pairwise intersubject correlation from observations by subjects array.
 
@@ -1981,6 +1982,7 @@ def isc(
         tail: (int) either 1 for one-tail or 2 for two-tailed test (default: 2)
         n_jobs: (int) The number of CPUs to use to do the computation. -1 means all CPUs.
         return_null: (bool) Return the permutation distribution along with the p-value; default False
+        sim_metric: (str) pairwise distance metric. See sklearn's pairwise_distances for valid inputs (default: correlation)
 
     Returns:
         stats: (dict) dictionary of permutation results ['correlation','p']
@@ -2000,7 +2002,7 @@ def isc(
     stats = {"isc": _compute_isc(data, metric=metric)}
 
     similarity = Adjacency(
-        1 - pairwise_distances(data.T, metric="correlation"), matrix_type="similarity"
+        1 - pairwise_distances(data.T, metric=sim_metric), matrix_type="similarity"
     )
 
     if method == "bootstrap":