{"action":"created","comment":{"url":"https://api.github.com/repos/pierreablin/picard/pulls/comments/194662126","pull_request_review_id":127873730,"id":194662126,"node_id":"MDI0OlB1bGxSZXF1ZXN0UmV2aWV3Q29tbWVudDE5NDY2MjEyNg==","diff_hunk":"@@ -206,3 +206,31 @@ def score_and_der(self, Y):\n def test_fun():\n     for fun in [Tanh(), Exp(), Cube()]:\n         check_density(fun)\n+\n+\n+def test_no_regression():\n+    n_tests = 10\n+    baseline = {}\n+    baseline['lap', True] = 17.\n+    baseline['lap', False] = 23.\n+    baseline['gauss', True] = 52.\n+    baseline['gauss', False] = 60.\n+    N, T = 10, 1000\n+    for mode in ['lap', 'gauss']:\n+        for ortho in [True, False]:\n+            n_iters = []\n+            for i in range(n_tests):\n+                rng = np.random.RandomState(i)\n+                if mode == 'lap':\n+                    S = rng.laplace(size=(N, T))\n+                else:\n+                    S = rng.randn(N, T)\n+                A = rng.randn(N, N)\n+                X = np.dot(A, S)\n+                _, _, _, n_iter = picard(X.copy(), 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