updating tests.

tests/test_emulator_interface.py

@@ -3,6 +3,7 @@
 from bloqade.atom_arrangement import Chain
 import numpy as np
 from itertools import product
+from math import isclose
 
 
 def test_zero_state():
@@ -44,8 +45,8 @@ def test_solution(N: int, phi: float, interaction: bool):
     rabi_freq = 2 * np.pi
     program = (
         Chain(N, lattice_spacing=6)
-        .rydberg.detuning.uniform.constant(1.0, 4.0)
-        .amplitude.uniform.constant(rabi_freq, 4)
+        # .rydberg.detuning.uniform.constant(1.0, 4.0)
+        .rydberg.rabi.amplitude.uniform.constant(rabi_freq, 4.0)
     )
 
     if phi != 0:
@@ -54,36 +55,44 @@ def test_solution(N: int, phi: float, interaction: bool):
     [emu] = program.bloqade.python().hamiltonian()
 
     times = np.linspace(0, 4, 101)
-    state_iter = emu.evolve(times=times, interaction_picture=interaction)
+    state_iter = emu.evolve(
+        times=times, interaction_picture=interaction, atol=1e-10, rtol=1e-14
+    )
 
     h = emu.hamiltonian.tocsr(0)
-
+    print(h.toarray())
     e, v = np.linalg.eigh(h.toarray())
 
     psi0 = emu.zero_state().data
 
     for state, time in zip(state_iter, times):
         assert str(state)
-        expected_data = v @ (np.diag(np.exp(-1j * e * time)) @ (v.T @ psi0))
+        expected_data = v @ (np.diag(np.exp(-1j * e * time)) @ (v.T.conj() @ psi0))
         data = state.data
 
-        expected_average = np.vdot(expected_data, h.dot(expected_data))
+        expected_average = np.vdot(expected_data, h.dot(expected_data)).real
         expected_variance = (
             np.vdot(expected_data, (h @ h).dot(expected_data)) - expected_average**2
-        )
+        ).real
+
+        print(emu.hamiltonian._apply(state.data, time) - h.dot(expected_data))
 
         average = emu.hamiltonian.average(state, time=time)
         variance = emu.hamiltonian.variance(state, time=time)
         average_2, variance_2 = emu.hamiltonian.average_and_variance(state, time=time)
-
-        assert np.allclose(data, expected_data), "failed at time {}".format(time)
-        assert np.allclose(average, expected_average), "failed at time {}".format(time)
-        assert np.allclose(average_2, expected_average), "failed at time {}".format(
-            time
-        )
-        assert np.allclose(variance, expected_variance), "failed at time {}".format(
-            time
-        )
-        assert np.allclose(variance_2, expected_variance), "failed at time {}".format(
-            time
-        )
+        overlap = np.vdot(data, expected_data)
+        assert isclose(overlap, 1.0, abs_tol=1e-7), f"failed data at time {time}"
+        assert isclose(
+            average, expected_average, rel_tol=1e-7, abs_tol=1e-7
+        ), f"failed average at time {time}"
+        assert isclose(
+            average_2, expected_average, rel_tol=1e-7, abs_tol=1e-7
+        ), f"failed average_2 at time {time}"
+        assert isclose(
+            variance, expected_variance, rel_tol=1e-7, abs_tol=1e-7
+        ), f"failed variance at time {time}"
+        assert isclose(
+            variance_2, expected_variance, rel_tol=1e-7, abs_tol=1e-7
+        ), f"failed variance_2 at time {time}"
+
+    # assert False