From ede3511e72b01d6b0cea0b859ac2fb797bf60a82 Mon Sep 17 00:00:00 2001 From: Talley Lambert Date: Thu, 21 Nov 2024 13:34:21 -0500 Subject: [PATCH] feat: add MDAEvent.slm_image (#204) * feat: add MDAEvent.slm_image * new assertion * fix 3.8 * add exposure --- src/useq/_mda_event.py | 48 +++++++++++++++++++++++++++++++++++++++++- tests/test_sequence.py | 19 +++++++++++++++++ 2 files changed, 66 insertions(+), 1 deletion(-) diff --git a/src/useq/_mda_event.py b/src/useq/_mda_event.py index f4b0327..5c69c30 100644 --- a/src/useq/_mda_event.py +++ b/src/useq/_mda_event.py @@ -14,7 +14,9 @@ Tuple, ) -from pydantic import Field, field_validator +import numpy as np +import numpy.typing as npt +from pydantic import Field, field_validator, model_validator from useq._actions import AcquireImage, AnyAction from useq._base_model import UseqModel @@ -52,6 +54,43 @@ def __eq__(self, _value: object) -> bool: return super().__eq__(_value) +class SLMImage(UseqModel): + """SLM Image in a MDA event. + + This object can be cast to a numpy.array using `np.asarray` or `np.array`. + + Attributes + ---------- + data: npt.ArrayLike + Image data. Anything that can be cast to a numpy array. For pydantic simplicity, + we mark this as Any, but in practice it should be numpy.typing.ArrayLike (which + is anything that can be cast to a numpy array using `np.asarray`). + device: Optional[str] + Optional name of the SLM device to use. If not provided, the "default" SLM + device should be used. (It is left to the backend to determine what device that + is). By default, `None`. + exposure: Optional[float] + Exposure time for the SLM specifically (if different from the detector), in + milliseconds. If not provided, the exposure on the owning MDAEvent should be + used. By default, `None`. + """ + + data: Any + device: Optional[str] = None + exposure: Optional[float] = None + + @model_validator(mode="before") + def _cast_data(cls, v: Any) -> Any: + """Can single, non-dict values to be the data.""" + if not isinstance(v, dict): + v = {"data": v} + return v + + def __array__(self, *args: Any, **kwargs: Any) -> npt.NDArray: + """Cast the image data to a numpy array.""" + return np.asarray(self.data, *args, **kwargs) + + class PropertyTuple(NamedTuple): """Three-tuple capturing a device, property, and value. @@ -110,6 +149,12 @@ class MDAEvent(UseqModel): z_pos : float | None Z position in microns. If not provided, implies use current position. By default, `None`. + slm_image : SLMImage | None + Image data to display on an SLM device. `SLMImage` is a simple pydantic object + with two attributes: `data` and `device`. `data` is the image data (anything + that can be cast to a numpy array), `device` is the name of the SLM device to + use. If not provided, the "default" SLM device should be used. By default, + `None`. sequence : MDASequence | None A reference to the [`useq.MDASequence`][] this event belongs to. This is a read-only attribute. By default, `None`. @@ -146,6 +191,7 @@ class MDAEvent(UseqModel): x_pos: Optional[float] = None y_pos: Optional[float] = None z_pos: Optional[float] = None + slm_image: Optional[SLMImage] = None sequence: Optional["MDASequence"] = Field(default=None, repr=False) properties: Optional[List[PropertyTuple]] = None metadata: Dict[str, Any] = Field(default_factory=dict) diff --git a/tests/test_sequence.py b/tests/test_sequence.py index 71efd45..3c7a846 100644 --- a/tests/test_sequence.py +++ b/tests/test_sequence.py @@ -22,6 +22,7 @@ ZRangeAround, ZRelativePositions, ) +from useq._mda_event import SLMImage from useq._position import RelativePosition _T = List[Tuple[Any, Sequence[float]]] @@ -462,3 +463,21 @@ def test_reset_event_timer() -> None: assert not events[1].reset_event_timer assert events[2].reset_event_timer assert not events[3].reset_event_timer + + +def test_slm_image() -> None: + data = [[0, 0], [1, 1]] + + # directly passing data + event = MDAEvent(slm_image=data) + assert isinstance(event.slm_image, SLMImage) + + # we can cast SLMIamge to a numpy array + assert isinstance(np.asarray(event.slm_image), np.ndarray) + np.testing.assert_array_equal(event.slm_image, np.array(data)) + + # variant that also specifies device label + event2 = MDAEvent(slm_image={"data": data, "device": "SLM"}) + assert event2.slm_image is not None + np.testing.assert_array_equal(event2.slm_image, np.array(data)) + assert event2.slm_image.device == "SLM"