Added optika.apertures.IsoscelesTrapezoidalAperture.

optika/_tests/test_apertures.py

@@ -226,3 +226,48 @@ class TestOctagonalAperture(
  AbstractTestAbstractOctagonalAperture,
 ):
  pass
+
+
+class AbstractTestAbstractIsoscelesTrapezoidalAperture(
+ AbstractTestAbstractPolygonalAperture,
+):
+ def test_x_left(self, a: optika.apertures.AbstractIsoscelesTrapezoidalAperture):
+ assert isinstance(na.as_named_array(a.x_left), na.AbstractScalar)
+
+ def test_x_right(self, a: optika.apertures.AbstractIsoscelesTrapezoidalAperture):
+ assert isinstance(na.as_named_array(a.x_right), na.AbstractScalar)
+
+ def test_angle(self, a: optika.apertures.AbstractIsoscelesTrapezoidalAperture):
+ assert isinstance(na.as_named_array(a.angle), na.AbstractScalar)
+
+
+x_left_parameterization = [
+ 25 * u.mm,
+ na.linspace(25, 30, axis="x_left", num=2) * u.mm,
+]
+
+
+@pytest.mark.parametrize(
+ argnames="a",
+ argvalues=[
+ optika.apertures.IsoscelesTrapezoidalAperture(
+ x_left=x_left,
+ x_right=50 * u.mm,
+ angle=45 * u.deg,
+ samples_wire=21,
+ active=active,
+ inverted=inverted,
+ transformation=transformation,
+ kwargs_plot=kwargs_plot,
+ )
+ for x_left in x_left_parameterization
+ for active in active_parameterization
+ for inverted in inverted_parameterization
+ for transformation in transform_parameterization
+ for kwargs_plot in test_plotting.kwargs_plot_parameterization
+ ],
+)
+class TestIsoscelesTrapezoidalAperture(
+ AbstractTestAbstractIsoscelesTrapezoidalAperture,
+):
+ pass

optika/apertures.py

@@ -16,6 +16,8 @@
  "AbstractRegularPolygonalAperture",
  "AbstractOctagonalAperture",
  "OctagonalAperture",
+ "AbstractIsoscelesTrapezoidalAperture",
+ "IsoscelesTrapezoidalAperture",
 ]
 
 
@@ -564,3 +566,99 @@ class OctagonalAperture(
  inverted: bool | na.AbstractScalar = False
  transformation: None | na.transformations.AbstractTransformation = None
  kwargs_plot: None | dict = None
+
+
+@dataclasses.dataclass(eq=False, repr=False)
+class AbstractIsoscelesTrapezoidalAperture(
+ AbstractPolygonalAperture,
+):
+ @property
+ @abc.abstractmethod
+ def x_left(self) -> na.ScalarLike:
+ """:math:`x` coordinate of the left base of the trapezoid"""
+
+ @property
+ @abc.abstractmethod
+ def x_right(self) -> na.ScalarLike:
+ """:math:`x` coordinate of the right base of the trapezoid"""
+
+ @property
+ @abc.abstractmethod
+ def angle(self) -> na.ScalarLike:
+ """angle between the two legs of the trapezoid"""
+
+ @property
+ def vertices(self) -> na.Cartesian3dVectorArray:
+ x_left = self.x_left
+ x_right = self.x_right
+ angle = self.angle
+
+ m = np.tan(angle / 2)
+ left = na.Cartesian3dVectorArray(
+ x=x_left,
+ y=m * x_left,
+ z=0 * x_left,
+ )
+ right = na.Cartesian3dVectorArray(
+ x=x_right,
+ y=m * x_right,
+ z=0 * x_right,
+ )
+
+ upper = na.stack([left, right], axis="vertex")
+
+ lower = upper[dict(vertex=slice(None, None, -1))]
+ lower = lower * na.Cartesian3dVectorArray(1, -1, 1)
+
+ result = na.concatenate([upper, lower], axis="vertex")
+
+ if self.transformation is not None:
+ result = self.transformation(result)
+
+ return result
+
+
+@dataclasses.dataclass(eq=False, repr=False)
+class IsoscelesTrapezoidalAperture(
+ AbstractIsoscelesTrapezoidalAperture,
+):
+ """
+ This aperture is useful if you want to break a circular aperture up
+ into different sectors.
+
+ .. jupyter-execute::
+
+ import matplotlib.pyplot as plt
+ import astropy.units as u
+ import astropy.visualization
+ import named_arrays as na
+ import optika
+
+ num_sectors = 8
+
+ roll = na.linspace(0, 360, axis="roll", num=num_sectors, endpoint=False) * u.deg
+
+ aperture = optika.apertures.IsoscelesTrapezoidalAperture(
+ x_left=10 * u.mm,
+ x_right=40 * u.mm,
+ angle=(360 * u.deg) / num_sectors,
+ transformation=na.transformations.TransformationList([
+ na.transformations.Cartesian3dTranslation(x=5 * u.mm),
+ na.transformations.Cartesian3dRotationZ(roll),
+ ])
+ )
+
+ with astropy.visualization.quantity_support():
+ plt.figure()
+ plt.gca().set_aspect("equal")
+ aperture.plot(components=("x", "y"), color="black")
+ """
+
+ x_left: na.ScalarLike = 0 * u.mm
+ x_right: na.ScalarLike = 0 * u.mm
+ angle: na.ScalarLike = 0 * u.deg
+ samples_wire: int = 101
+ active: bool | na.AbstractScalar = True
+ inverted: bool | na.AbstractScalar = False
+ transformation: None | na.transformations.AbstractTransformation = None
+ kwargs_plot: None | dict = None