feat: Add function to resample a driven control (#201)

Alternative to #200. Even though this one is a bit less consistent with BOULDER OPAL, I think it's better. For a start, it means the user can also benefit from resampling for the export-to-file function too, which I would have thought should be very useful. Also, I don't think consistency with BOULDER OPAL is that important here, because DrivenControl is a very different beast to a plain old pulse.

Author: charmasaur

qctrlopencontrols/driven_controls/driven_control.py

@@ -330,6 +330,51 @@ def duration(self) -> float:
 
         return np.sum(self.durations)
 
+    def resample(self, time_step: float, name: Optional[str] = None) -> "DrivenControl":
+        r"""
+        Returns a new driven control obtained by resampling this control.
+
+        Parameters
+        ----------
+        time_step : float
+            The time step to use for resampling, :math:`\delta t`.
+        name : str, optional
+            The name for the new control. Defaults to ``None``.
+
+        Returns
+        -------
+        DrivenControl
+            A new driven control, sampled at the specified rate. The durations of the new control
+            are all equal to :math:`\delta t`. The total duration of the new control might be
+            slightly larger than the original duration, if the time step doesn't exactly divide the
+            original duration.
+        """
+        check_arguments(
+            time_step > 0,
+            "Time step must be positive.",
+            {"time_step": time_step},
+        )
+        check_arguments(
+            time_step <= self.duration,
+            "Time step must be less than or equal to the original duration.",
+            {"time_step": time_step},
+            {"duration": self.duration},
+        )
+
+        count = int(np.ceil(self.duration / time_step))
+        durations = [time_step] * count
+        times = np.arange(count) * time_step
+
+        indices = np.digitize(times, bins=np.cumsum(self.durations))
+
+        return DrivenControl(
+            durations,
+            self.rabi_rates[indices],
+            self.azimuthal_angles[indices],
+            self.detunings[indices],
+            name,
+        )
+
     def _qctrl_expanded_export_content(self, coordinates: str) -> Dict:
         """
         Prepare the content to be saved in Q-CTRL expanded format.

tests/test_driven_controls.py

@@ -406,3 +406,45 @@ def test_pretty_print():
     expected_string = "\n".join(_pretty_string)
 
     assert str(driven_control) == expected_string
+
+
+def test_resample_exact():
+    driven_control = DrivenControl(
+        rabi_rates=[0, 2],
+        azimuthal_angles=[1.5, 0.5],
+        detunings=[1.3, 2.3],
+        durations=[1, 1],
+        name="control",
+    )
+
+    new_driven_control = driven_control.resample(0.5)
+
+    assert len(new_driven_control.durations) == 4
+
+    assert np.allclose(new_driven_control.durations, 0.5)
+    assert np.allclose(new_driven_control.rabi_rates, [0, 0, 2, 2])
+    assert np.allclose(new_driven_control.azimuthal_angles, [1.5, 1.5, 0.5, 0.5])
+    assert np.allclose(new_driven_control.detunings, [1.3, 1.3, 2.3, 2.3])
+
+
+def test_resample_inexact():
+    driven_control = DrivenControl(
+        rabi_rates=[0, 2],
+        azimuthal_angles=[1.5, 0.5],
+        detunings=[1.3, 2.3],
+        durations=[1, 1],
+        name="control",
+    )
+
+    new_driven_control = driven_control.resample(0.3)
+
+    assert len(new_driven_control.durations) == 7
+
+    assert np.allclose(new_driven_control.durations, 0.3)
+    assert np.allclose(new_driven_control.rabi_rates, [0, 0, 0, 0, 2, 2, 2])
+    assert np.allclose(
+        new_driven_control.azimuthal_angles, [1.5, 1.5, 1.5, 1.5, 0.5, 0.5, 0.5]
+    )
+    assert np.allclose(
+        new_driven_control.detunings, [1.3, 1.3, 1.3, 1.3, 2.3, 2.3, 2.3]
+    )