Fix XRayTransform2D projection dtype and docs (#557)

Co-authored-by: Brendt Wohlberg <brendt@ieee.org>

scico/linop/xray/_xray.py

@@ -27,7 +27,7 @@
 
 
 class XRayTransform2D(LinearOperator):
-    """Parallel ray, single axis, 2D X-ray projector.
+    r"""Parallel ray, single axis, 2D X-ray projector.
 
     This implementation approximates the projection of each rectangular
     pixel as a boxcar function (whereas the exact projection is a
@@ -42,6 +42,9 @@ class XRayTransform2D(LinearOperator):
     accumulation of pixel values into bins (equivalently, makes the
     linear operator sparse).
 
+    Warning: The default pixel spacing is :math:`\sqrt{2}/2` (rather
+    than 1) in order to satisfy the aforementioned spacing requirement.
+
     `x0`, `dx`, and `y0` should be expressed in units such that the
     detector spacing `dy` is 1.0.
     """
@@ -64,9 +67,11 @@ def __init__(
                 corresponds to summing columns, and an angle of pi/4
                 corresponds to summing along antidiagonals.
             x0: (x, y) position of the corner of the pixel `im[0,0]`. By
-                default, `(-input_shape / 2, -input_shape / 2)`.
-            dx: Image pixel side length in x- and y-direction. Should be
-                <= 1.0 in each dimension. By default, [1.0, 1.0].
+                default, `(-input_shape * dx[0] / 2, -input_shape * dx[1] / 2)`.
+            dx: Image pixel side length in x- and y-direction. Must be
+                set so that the width of a projected pixel is never
+                larger than 1.0. By default, [:math:`\sqrt{2}/2`,
+                :math:`\sqrt{2}/2`].
             y0: Location of the edge of the first detector bin. By
                 default, `-det_count / 2`
             det_count: Number of elements in detector. If ``None``,
@@ -111,25 +116,36 @@ def __init__(
 
         super().__init__(
             input_shape=self.input_shape,
+            input_dtype=np.float32,
             output_shape=self.output_shape,
+            output_dtype=np.float32,
             eval_fn=self.project,
             adj_fn=self.back_project,
         )
 
     def project(self, im: ArrayLike) -> snp.Array:
-        """Compute X-ray projection."""
+        """Compute X-ray projection, equivalent to `H @ im`.
+
+        Args:
+            im: Input array representing the image to project.
+        """
         return XRayTransform2D._project(im, self.x0, self.dx, self.y0, self.ny, self.angles)
 
     def back_project(self, y: ArrayLike) -> snp.Array:
-        """Compute X-ray back projection"""
+        """Compute X-ray back projection, equivalent to `H.T @ y`.
+
+        Args:
+            y: Input array representing the sinogram to back project.
+        """
         return XRayTransform2D._back_project(y, self.x0, self.dx, self.nx, self.y0, self.angles)
 
     @staticmethod
     @partial(jax.jit, static_argnames=["ny"])
     def _project(
         im: ArrayLike, x0: ArrayLike, dx: ArrayLike, y0: float, ny: int, angles: ArrayLike
     ) -> snp.Array:
-        r"""
+        r"""Compute X-ray projection.
+
         Args:
             im: Input array, (M, N).
             x0: (x, y) position of the corner of the pixel im[0,0].
@@ -146,8 +162,11 @@ def _project(
         # ignored, while inds < 0 wrap around. So we set inds < 0 to ny.
         inds = jnp.where(inds >= 0, inds, ny)
 
+        # avoid incompatible types in the .add (scatter operation)
+        weights = weights.astype(im.dtype)
+
         y = (
-            jnp.zeros((len(angles), ny))
+            jnp.zeros((len(angles), ny), dtype=im.dtype)
             .at[jnp.arange(len(angles)).reshape(-1, 1, 1), inds]
             .add(im * weights)
         )
@@ -161,7 +180,8 @@ def _project(
     def _back_project(
         y: ArrayLike, x0: ArrayLike, dx: ArrayLike, nx: Shape, y0: float, angles: ArrayLike
     ) -> ArrayLike:
-        r"""
+        r"""Compute X-ray back projection.
+
         Args:
             y: Input projection, (num_angles, N).
             x0: (x, y) position of the corner of the pixel im[0,0].
@@ -259,10 +279,6 @@ class XRayTransform3D(LinearOperator):
 
     :meth:`XRayTransform3D.matrices_from_euler_angles` can help to
     make these geometry arrays.
-
-
-
-
     """
 
     def __init__(
@@ -279,7 +295,7 @@ def __init__(
         """
 
         self.input_shape: Shape = input_shape
-        self.matrices = matrices
+        self.matrices = jnp.asarray(matrices, dtype=np.float32)
         self.det_shape = det_shape
         self.output_shape = (len(matrices), *det_shape)
         super().__init__(

scico/test/linop/xray/test_xray.py

@@ -49,7 +49,7 @@ def test_apply():
 def test_apply_adjoint():
     im_shape = (12, 13)
     num_angles = 10
-    x = jnp.ones(im_shape)
+    x = jnp.ones(im_shape, dtype=jnp.float32)
 
     angles = jnp.linspace(0, jnp.pi, num=num_angles, endpoint=False)
 
@@ -81,6 +81,7 @@ def test_3d_scaling():
     # default spacing
     M = XRayTransform3D.matrices_from_euler_angles(input_shape, output_shape, "X", [0.0])
     H = XRayTransform3D(input_shape, matrices=M, det_shape=output_shape)
+
     # fmt: off
     truth = jnp.array(
         [[[0.0, 0.0, 0.0, 0.0],