sparsify_matrix.py

useful_scripts/sparsify_matrix.py

@@ -0,0 +1,36 @@
+# Sebastian Raschka 2014
+#
+# Sparsifying a matrix by Zeroing out all elements but the top k elements in a row.
+# The matrix could be a distance or similarity matrix (e.g., kernel matrix in kernel PCA),
+# where we are interested to keep the top k neighbors.
+
+print('Sparsify a matrix by zeroing all elements but the top 2 values in a row.\n')
+
+A = np.array([[1,2,3,4,5],[9,8,6,4,5],[3,1,7,8,9]])
+
+print('Before:\n%s\n' %A)
+
+
+k = 2 # keep top k neighbors
+for row in A:
+    sort_idx = np.argsort(row)[::-1] # get indexes of sort order (high to low)
+    for i in sort_idx[k:]:
+        row[i]=0
+        
+print('After:\n%s\n' %A)
+
+
+"""
+Sparsify a matrix by zeroing all elements but the top 2 values in a row.
+
+Before:
+[[1 2 3 4 5]
+ [9 8 6 4 5]
+ [3 1 7 8 9]]
+
+After:
+[[0 0 0 4 5]
+ [9 8 0 0 0]
+ [0 0 0 8 9]]
+
+"""