add software license for IDS + author credit

Author: joshuabmoore

pyspi/lib/ids/LICENSE.txt

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2025 Adityanarayanan Radhakrishnan
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

pyspi/lib/ids/dependence.py

@@ -1,11 +1,20 @@
+"""
+Interdependence Score (IDS) computation.
+Based on the work by Adityanarayanan Radhakrishnan (MIT License)
+Original: https://github.com/aradha/interdependence_scores
+Modified for use in pyspi package.
+"""
 from .numpy_dependence import compute_IDS_numpy
 
 def compute_IDS(X, Y=None, num_terms=6, p_norm='max', 
                 p_val=False, num_tests=100, bandwidth_term=1/2):
     """Compute IDS between all pairs of variables in X (or between X and Y).
     
-    Taken from the implementation in: https://github.com/aradha/interdependence_scores
+    This is a modified version of the implementation from:
+    https://github.com/aradha/interdependence_scores
     
+    Original author: Adityanarayanan Radhakrishnan
+    License: MIT (see LICENSE.txt)
 
     Parameters:
         X: np.ndarray or torch.Tensor
@@ -19,4 +28,4 @@ def compute_IDS(X, Y=None, num_terms=6, p_norm='max',
         IDS matrix, p-value matrix (if p_val=True)
     """
     return compute_IDS_numpy(X, Y=Y, num_terms=num_terms, p_norm=p_norm, 
-                                 p_val=p_val, num_tests=num_tests, bandwidth_term=bandwidth_term)
+                                 p_val=p_val, num_tests=num_tests, bandwidth_term=bandwidth_term)

pyspi/lib/ids/numpy_dependence.py

@@ -1,3 +1,8 @@
+"""
+Interdependence Score (IDS) computation.
+Based on the work by Adityanarayanan Radhakrishnan (MIT License)
+Original: https://github.com/aradha/interdependence_scores
+"""
 import numpy as np 
 import math
 import sys