Complete migration: convert all remaining np.dot to @ operator in test files and markov module

Co-authored-by: mmcky <[email protected]>

Author: Copilot

quantecon/markov/gth_solve.py

@@ -83,12 +83,12 @@ def gth_solve(A, overwrite=False, use_jit=True):
             break
         A1[k+1:n, k] /= scale
 
-        A1[k+1:n, k+1:n] += np.dot(A1[k+1:n, k:k+1], A1[k:k+1, k+1:n])
+        A1[k+1:n, k+1:n] += A1[k+1:n, k:k+1] @ A1[k:k+1, k+1:n]
 
     # === Backward substitution === #
     x[n-1] = 1
     for k in range(n-2, -1, -1):
-        x[k] = np.dot(x[k+1:n], A1[k+1:n, k])
+        x[k] = x[k+1:n] @ A1[k+1:n, k]
 
     # === Normalization === #
     x /= np.sum(x)

quantecon/markov/tests/test_core.py

@@ -225,12 +225,12 @@ def test_left_eigen_vec(self):
         stationary_distributions = self.stationary
 
         if self.n_stat_dists == 1:
-            assert_allclose(np.dot(stationary_distributions, mc.P),
+            assert_allclose(stationary_distributions @ mc.P,
                             stationary_distributions, atol=self.TOL)
         else:
             for i in range(self.n_stat_dists):
                 curr_v = stationary_distributions[i, :]
-                assert_allclose(np.dot(curr_v, mc.P), curr_v, atol=self.TOL)
+                assert_allclose(curr_v @ mc.P, curr_v, atol=self.TOL)
 
 
 def test_simulate_shape():

quantecon/markov/tests/test_gth_solve.py

@@ -108,7 +108,7 @@ def __call__(self, x):
 
 class StationaryDistLeftEigenVec(AddDescription):
     def __call__(self, A, x):
-        assert_allclose(np.dot(x, A), x, atol=TOL)
+        assert_allclose(x @ A, x, atol=TOL)
 
 
 class StationaryDistEqualToKnown(AddDescription):

quantecon/tests/test_kalman.py

@@ -17,8 +17,8 @@ def setup_method(self):
         self.G = np.eye(2) * .5
         self.H = np.eye(2) * np.sqrt(0.2)
 
-        self.Q = np.dot(self.C, self.C.T)
-        self.R = np.dot(self.H, self.H.T)
+        self.Q = self.C @ self.C.T
+        self.R = self.H @ self.H.T
 
         ss = LinearStateSpace(self.A, self.C, self.G, self.H)
 
@@ -42,7 +42,7 @@ def test_stationarity(self):
 
             # Compute the kalmain gain and sigma infinity according to the
             # recursive equations and compare
-            kal_recursion = np.dot(A, sig_inf).dot(G.T).dot(mat_inv)
+            kal_recursion = (A @ sig_inf).dot(G.T).dot(mat_inv)
             sig_recursion = (A.dot(sig_inf).dot(A.T) -
                                 kal_recursion.dot(G).dot(sig_inf).dot(A.T) + Q)
 
@@ -76,7 +76,7 @@ def test_update_nonstationary(self):
         kf.update(y_observed)
 
         mat_inv = np.linalg.inv(G.dot(curr_sigma).dot(G.T) + R)
-        curr_k = np.dot(A, curr_sigma).dot(G.T).dot(mat_inv)
+        curr_k = (A @ curr_sigma).dot(G.T).dot(mat_inv)
         new_sigma = (A.dot(curr_sigma).dot(A.T) -
                     curr_k.dot(G).dot(curr_sigma).dot(A.T) + Q)
 

quantecon/tests/test_lqcontrol.py

@@ -83,7 +83,7 @@ def test_stationary_mat(self):
 
         for method in self.methods:
             P, F, d = lq_mat.stationary_values(method=method)
-            val_func_lq = np.dot(x0, P).dot(x0)
+            val_func_lq = (x0 @ P).dot(x0)
 
             assert_allclose(f_answer, F, atol=1e-3)
             assert_allclose(val_func_lq, val_func_answer, atol=1e-3)

quantecon/tests/test_matrix_eqn.py

@@ -34,5 +34,5 @@ def test_solve_discrete_lyapunov_complex():
 
     X = qme.solve_discrete_lyapunov(A, B)
 
-    assert_allclose(np.dot(np.dot(A, X), A.conj().transpose()) - X, -B,
+    assert_allclose((A @ X @ A.conj().transpose()) - X, -B,
                     atol=1e-15)

quantecon/tests/test_ricatti.py

@@ -62,7 +62,7 @@ def dare_tjm_3(method):
     B = I
     R = [[1, r],
          [r, r*r]]
-    Q = I - np.dot(A.T, A) + np.dot(A.T, np.linalg.solve(R + I, A))
+    Q = I - (A.T @ A) + (A.T @ np.linalg.solve(R + I, A))
     X = solve_discrete_riccati(A, B, Q, R, method=method)
     Y = np.identity(2)
     assert_allclose(X, Y, atol=1e-07)