Feat: Add WaveformPulse

CHANGELOG.md

@@ -1,3 +1,8 @@
+## [Unreleased]
+### Added
+- Added `WaveformPulse` to allow for pre-defined waveforms.
+
+
 ## [0.3.6]
 ### Changed
 - Modified `MWChannel` to also have `RF_frequency` and `LO_frequency` to match the signature of `IQChannel`.

quam/components/pulses.py

@@ -1,7 +1,7 @@
 from abc import ABC, abstractmethod
 import numbers
 import warnings
-from typing import Any, ClassVar, Dict, List, Union, Tuple
+from typing import Any, ClassVar, Dict, List, Optional, Union, Tuple
 import numpy as np
 
 from quam.core import QuamComponent, quam_dataclass
@@ -398,6 +398,48 @@ def integration_weights_function(self) -> List[Tuple[Union[complex, float], int]
         }
 
 
+@quam_dataclass
+class WaveformPulse(Pulse):
+    """Pulse that uses a pre-defined waveform, as opposed to a function.
+
+    For a single channel, only `waveform_I` is required.
+    For an IQ channel, both `waveform_I` and `waveform_Q` are required.
+
+    The length of the pulse is derived from the length of `waveform_I`.
+
+    Args:
+        waveform_I (list[float]): The in-phase waveform.
+        waveform_Q (list[float], optional): The quadrature waveform.
+    """
+
+    waveform_I: List[float]  # pyright: ignore
+    waveform_Q: Optional[List[float]] = None
+    # Length is derived from the waveform_I length, but still needs to be declared
+    # to satisfy the dataclass, but we'll override its behavior
+    length: Optional[int] = None  # pyright: ignore
+
+    @property
+    def length(self):  # noqa: 811
+        return len(self.waveform_I)
+
+    @length.setter
+    def length(self, length: Optional[int]):
+        if length is not None and not isinstance(length, property):
+            raise AttributeError(f"length is not writable with value {length}")
+
+    def waveform_function(self):
+        if self.waveform_Q is None:
+            return np.array(self.waveform_I)
+        return np.array(self.waveform_I) + 1.0j * np.array(self.waveform_Q)
+
+    def to_dict(
+        self, follow_references: bool = False, include_defaults: bool = False
+    ) -> Dict[str, Any]:
+        d = super().to_dict(follow_references, include_defaults)
+        d.pop("length")
+        return d
+
+
 @quam_dataclass
 class DragGaussianPulse(Pulse):
     """Gaussian-based DRAG pulse that compensate for the leakage and AC stark shift.

tests/components/pulses/test_waveform_pulse.py

@@ -0,0 +1,36 @@
+import numpy as np
+import pytest
+from quam.components.pulses import WaveformPulse
+
+
+def test_waveform_pulse_length():
+    pulse = WaveformPulse(waveform_I=[1, 2, 3])
+    assert pulse.length == 3
+
+    pulse.waveform_I = [1, 2, 3, 4]
+
+    with pytest.raises(AttributeError):
+        pulse.length = 5
+
+    assert pulse.length == 4
+
+
+def test_waveform_pulse_IQ():
+    pulse = WaveformPulse(waveform_I=[1, 2, 3], waveform_Q=[4, 5, 6])
+    assert np.all(
+        pulse.waveform_function() == np.array([1, 2, 3]) + 1.0j * np.array([4, 5, 6])
+    )
+
+
+def test_waveform_pulse_IQ_mismatch():
+    pulse = WaveformPulse(waveform_I=[1, 2, 3], waveform_Q=[4, 5])
+    with pytest.raises(ValueError):
+        pulse.waveform_function()
+
+
+def test_waveform_pulse_to_dict():
+    pulse = WaveformPulse(waveform_I=[1, 2, 3], waveform_Q=[4, 5, 6])
+    assert pulse.to_dict() == {
+        "waveform_I": [1, 2, 3],
+        "waveform_Q": [4, 5, 6],
+    }