.gitignore

+*.egg-info
+/build/
+__pycache__
+/temp/
\ No newline at end of file

.gitlab-ci.yml

+image: ubuntu:latest
+
+stages:
+  - code_embed
+
+variables:
+  GIT_STRATEGY: clone
+
+code_embedder:
+  stage: code_embed
+  script:
+    - echo "Personal a" 
+    - cd code-embedder/
+    - poetry install --only main
+    - README_PATHS=$(find .. -maxdepth 1 -name "*.md" -print)
+    - poetry run python ./src/main.py --readme-paths $README_PATHS
+    - cd ..
+    - README_PATHS=$(find . -maxdepth 1 -name "*.md" -print)
+    - git add $README_PATHS
+    - git diff --staged
+    - export BRANCH_NAME="${CI_MERGE_REQUEST_SOURCE_BRANCH_NAME:-$CI_COMMIT_REF_NAME}"
+    - echo "branch name $BRANCH_NAME"
+    - git remote set-url origin "https://oauth2:${PERSONAL_ACCESS_TOKEN}@${CI_SERVER_HOST}/${CI_PROJECT_PATH}.git"
+    - echo "https://oauth2:${PERSONAL_ACCESS_TOKEN}@${CI_SERVER_HOST}/${CI_PROJECT_PATH}.git"
+    - if ! git diff --cached --exit-code; then
+        git commit -m "Apply Code Embedder";
+        git push origin HEAD:$BRANCH_NAME;
+      else
+        echo "No changes to commit";
+      fi
+
+  before_script:
+    - apt-get update && apt-get install -y curl git python3 python3-pip
+    - curl -sSL https://install.python-poetry.org | python3 -
+    - export PATH="$HOME/.local/bin:$PATH"
+    - git clone https://github.com/kvankova/code-embedder.git
+    - git config --global user.email $GITLAB_USER_EMAIL
+    - git config --global user.name $GITLAB_USER_NAME
+  only:
+    - merge_requests
+    
\ No newline at end of file

.python-version

+3.10

README.md

+# Object Placement
+![](/temp/logo.svg)
+## For Circular CT Trajectories using Local Cylindrical Xray Transforms / CyXTraX
+
+To install just use uv.
+```bash
+uv venv
+uv run scripts/01_circular_trajectory.py 
+```
+
+## Examples
+
+```python:../scripts/01_circular_trajectory.py:o:main
+def main():
+
+    fod_mm = jnp.array([1000,])
+    fdd_mm = jnp.array([2000,])
+    alpha_rad = jnp.linspace(0, jnp.pi, 100).reshape((-1, 1))
+
+    source, orientation_source, detector, orientation_detector = circular_trajectory(fod_mm, fdd_mm, alpha_rad)
+    source, orientation_source, detector, orientation_detector = add_world_orign(
+        source, orientation_source, detector, orientation_detector, jnp.array([1, 2., -1.]), x_90_quat)
+    detector, orientation_detector = add_offset(detector, orientation_detector, jnp.array([1, 20., -1.]), zero_quat)
+    
+    print(source.shape)
+    print(orientation_detector.shape)
+
+    api = API()
+
+    for i in range(source.shape[0]):
+        api.translate('S', source[i, 0], source[i, 1], source[i, 2])
+        api.translate('D', detector[i, 0], detector[i, 1], detector[i, 2])
+        api.rotate_from_quat('D', orientation_detector[i])
+        api.rotate_from_quat('S', orientation_source[i])
+```
+
+```python:../scripts/02_object_placment.py:o:main
+def main():
+    files = list(FOLDER.glob('*.h5'))
+    map_path = files[0]
+    maps, points, mesh_object_list = load_atlas(map_path)
+    number_of_projection = 2000
+
+    obj_place = CircularTrajectoryOptimization(maps, points, number_of_projection=number_of_projection)
+    obj_place.alpha_x_deg.value = jnp.array([1.,])
+
+    grid_num = 128
+
+    angle_0 = 40
+    angle_1 = 180
+
+    grid_y = jnp.linspace(-angle_0, angle_0, grid_num, endpoint=True)
+    grid_z = jnp.linspace(-angle_1, angle_1, grid_num, endpoint=True)
+    grid_array = jnp.zeros((grid_num, grid_num, number_of_projection, maps.shape[2]))
+
+
+    for i in range(grid_num):
+        obj_place.alpha_x_deg.value = jnp.ones((grid_num, 1)) * grid_y[i]
+        obj_place.beta_y_deg.value = grid_z.reshape((-1, 1))
+        obj_place.origin.value = jnp.zeros((grid_num, 3))
+        return_array = obj_place()
+        grid_array = grid_array.at[i].set(return_array)
+        print(i)
+    
+    print(grid_array.shape)
+
+    grid_array_std = jnp.std(grid_array, 2)
+    print(grid_array_std.shape)
+
+    grid_array_std = jnp.std(grid_array, 3)
+    print(grid_array_std.shape)
+
+    mean_std_grid = jnp.mean(jnp.std(grid_array, 2), 2)
+    plot_map(mean_std_grid, [angle_0, angle_1], TEMP_FOLDER, 'Mean STD')
+
+    mean_mean_grid = jnp.mean(jnp.mean(grid_array, 2), 2)
+    plot_map(mean_mean_grid, [angle_0, angle_1], TEMP_FOLDER, 'Mean')
+
+    std_std_grid = jnp.std(jnp.std(grid_array, 3), 2)
+    plot_map(std_std_grid, [angle_0, angle_1], TEMP_FOLDER, 'STD')
+
+    std_mean_grid = jnp.std(jnp.mean(grid_array, 3), 2)
+    plot_map(std_mean_grid, [angle_0, angle_1], TEMP_FOLDER, 'STD Mean')
+```
+![](/temp/meanstd_map.png)
\ No newline at end of file

pyproject.toml

+[project]
+name = "cyxtrax_object"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+    "artist_pythonlib ; sys_platform == 'windows'",
+    "cyxtrax",
+    "evosax>=0.1.6 ; sys_platform == 'linux'",
+    "flax>=0.10.1",
+    "jax>=0.4.35 ; sys_platform == 'windows'",
+    "jax[cuda12]>=0.4.35 ; sys_platform == 'linux'",
+]
+
+[tool.uv.sources]
+cyxtrax = { git = "https://mygit.th-deg.de/roboct-public/xraytransformstudies/cyxtrax" }
+artist-pythonlib = { git = "https://mygit.th-deg.de/roboct-public/artist-api" }
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"

scripts/01_circular_trajectory.py

+from cyxtrax_object import (
+    circular_trajectory,
+    add_world_orign,
+    zero_quat,
+    x_90_quat,
+    add_offset,
+)
+from jax import numpy as jnp
+from artistlib import API
+
+
+def main():
+    fod_mm = jnp.array(
+        [
+            1000,
+        ]
+    )
+    fdd_mm = jnp.array(
+        [
+            2000,
+        ]
+    )
+    alpha_rad = jnp.linspace(0, jnp.pi, 100).reshape((-1, 1))
+
+    source, orientation_source, detector, orientation_detector = circular_trajectory(
+        fod_mm, fdd_mm, alpha_rad
+    )
+    source, orientation_source, detector, orientation_detector = add_world_orign(
+        source,
+        orientation_source,
+        detector,
+        orientation_detector,
+        jnp.array([1, 2.0, -1.0]),
+        x_90_quat,
+    )
+    detector, orientation_detector = add_offset(
+        detector, orientation_detector, jnp.array([1, 20.0, -1.0]), zero_quat
+    )
+
+    print(source.shape)
+    print(orientation_detector.shape)
+
+    api = API()
+
+    for i in range(source.shape[0]):
+        api.translate("S", source[i, 0], source[i, 1], source[i, 2])
+        api.translate("D", detector[i, 0], detector[i, 1], detector[i, 2])
+        api.rotate_from_quat("D", orientation_detector[i])
+        api.rotate_from_quat("S", orientation_source[i])
+
+
+if __name__ == "__main__":
+    main()

scripts/02_object_placment.py

+from cyxtrax_object import CircularTrajectoryOptimization, plot_map
+
+from cyxtrax.io.load_maps import load_atlas
+from pathlib import Path
+from jax import numpy as jnp
+
+
+FOLDER = Path(r"C:\data\xray_transform")
+TEMP_FOLDER = Path("./temp/")
+
+
+def main():
+    files = list(FOLDER.glob("*.h5"))
+    map_path = files[0]
+    maps, points, mesh_object_list = load_atlas(map_path)
+    number_of_projection = 2000
+
+    obj_place = CircularTrajectoryOptimization(
+        maps, points, number_of_projection=number_of_projection
+    )
+    obj_place.alpha_x_deg.value = jnp.array(
+        [
+            1.0,
+        ]
+    )
+
+    grid_num = 128
+
+    angle_0 = 40
+    angle_1 = 180
+
+    grid_y = jnp.linspace(-angle_0, angle_0, grid_num, endpoint=True)
+    grid_z = jnp.linspace(-angle_1, angle_1, grid_num, endpoint=True)
+    grid_array = jnp.zeros((grid_num, grid_num, number_of_projection, maps.shape[2]))
+
+    for i in range(grid_num):
+        obj_place.alpha_x_deg.value = jnp.ones((grid_num, 1)) * grid_y[i]
+        obj_place.beta_y_deg.value = grid_z.reshape((-1, 1))
+        obj_place.origin.value = jnp.zeros((grid_num, 3))
+        return_array = obj_place()
+        grid_array = grid_array.at[i].set(return_array)
+        print(i)
+
+    print(grid_array.shape)
+
+    grid_array_std = jnp.std(grid_array, 2)
+    print(grid_array_std.shape)
+
+    grid_array_std = jnp.std(grid_array, 3)
+    print(grid_array_std.shape)
+
+    mean_std_grid = jnp.mean(jnp.std(grid_array, 2), 2)
+    plot_map(mean_std_grid, [angle_0, angle_1], TEMP_FOLDER, "Mean STD")
+
+    mean_mean_grid = jnp.mean(jnp.mean(grid_array, 2), 2)
+    plot_map(mean_mean_grid, [angle_0, angle_1], TEMP_FOLDER, "Mean")
+
+    std_std_grid = jnp.std(jnp.std(grid_array, 3), 2)
+    plot_map(std_std_grid, [angle_0, angle_1], TEMP_FOLDER, "STD")
+
+    std_mean_grid = jnp.std(jnp.mean(grid_array, 3), 2)
+    plot_map(std_mean_grid, [angle_0, angle_1], TEMP_FOLDER, "STD Mean")
+
+
+if __name__ == "__main__":
+    main()

scripts/03_evosax.py

+from cyxtrax_object import CircularTrajectoryOptimization
+
+from CyXTraX.io.load_maps import load_atlas
+from pathlib import Path
+from jax import numpy as jnp, lax, random
+from flax import nnx
+from evosax import ParameterReshaper
+from evosax.strategies.ars import ARS
+from evosax import CMA_ES
+
+
+MAP_FOLDER = Path(r"C:\data\XrayTransform")
+TEMP_FOLDER = Path(r"./temp")
+POP_SIZE = 100
+ITERATIONS = 100
+EPOCH = 25
+
+
+def main():
+    files = list(MAP_FOLDER.glob("*.h5"))
+    map_path = files[0]
+    maps, points, mesh_object_list = load_atlas(map_path)
+    number_of_projection = 2000
+
+    obj_place = CircularTrajectoryOptimization(
+        maps, points, number_of_projection=number_of_projection, only_orientation=False
+    )
+    params = nnx.state(obj_place, nnx.Param)
+    print(params)
+
+    param_reshaper = ParameterReshaper(params)
+
+    strategy = ARS(popsize=100, num_dims=param_reshaper.total_params)
+    strategy = CMA_ES(popsize=100, num_dims=param_reshaper.total_params)
+
+    es_params = strategy.default_params
+    rng = random.PRNGKey(42)
+    state = strategy.initialize(rng, es_params)
+
+    def es_step(state_input, tmp):
+        rng, state = state_input
+        rng, rng_iter = random.split(rng)
+        x, state = strategy.ask(rng_iter, state, es_params)
+        weights = param_reshaper.reshape(x)
+        model = nnx.clone(obj_place)
+        nnx.update(model, weights)
+        fitness = model()
+        fitness = jnp.std(jnp.std(fitness, 1), 1)
+        state = strategy.tell(x, fitness, state, es_params)
+        return [rng, state], fitness[jnp.argmin(fitness)]
+
+    for i in range(ITERATIONS // EPOCH):
+        [rng, state], scan_out = lax.scan(es_step, [rng, state], [jnp.zeros(EPOCH)])
+        print(f"Best Member at Iteration {i * EPOCH}: {state.best_member}")
+
+
+if __name__ == "__main__":
+    main()

scripts/04_generate_ct_data.py

+from cyxtrax_object import (
+    circular_trajectory,
+    add_world_orign,
+    zero_quat,
+    x_90_quat,
+    add_offset,
+)
+from jax import numpy as jnp
+from artistlib import API
+from cyxtrax.simulation.artist_bridge import set_cone_mode
+
+
+def main():
+    fod_mm = jnp.array(
+        [
+            1000,
+        ]
+    )
+    fdd_mm = jnp.array(
+        [
+            2000,
+        ]
+    )
+    alpha_rad = jnp.linspace(0, jnp.pi, 100).reshape((-1, 1))
+
+    source, orientation_source, detector, orientation_detector = circular_trajectory(
+        fod_mm, fdd_mm, alpha_rad
+    )
+    source, orientation_source, detector, orientation_detector = add_world_orign(
+        source,
+        orientation_source,
+        detector,
+        orientation_detector,
+        jnp.array([1, 2.0, -1.0]),
+        x_90_quat,
+    )
+    detector, orientation_detector = add_offset(
+        detector, orientation_detector, jnp.array([1, 20.0, -1.0]), zero_quat
+    )
+
+    print(source.shape)
+    print(orientation_detector.shape)
+
+    api = API()
+    set_cone_mode(api)
+
+    for i in range(source.shape[0]):
+        api.translate("S", source[i, 0], source[i, 1], source[i, 2])
+        api.translate("D", detector[i, 0], detector[i, 1], detector[i, 2])
+        api.rotate_from_quat("D", orientation_detector[i])
+        api.rotate_from_quat("S", orientation_source[i])
+
+
+if __name__ == "__main__":
+    main()

setup.cfg

+[metadata]
+name = cyxtrax_object
+version = 0.1.0
+description = A Python module to play with obeject orientation for circular trajectories using local cylindrical xray transform maps or atlases.
+author = Simon Wittl
+author_email = simon.wittl@th-deg.de / simonwittl@gmail.com
+url = https://mygit.th-deg.de/roboct/xraytrafo
+
+[options]
+packages = find:
+include_package_data = True  # Ensures data files are included
+zip_safe = False
+
+
+install_requires =
+    CyXTraX
+    jaxlib
+    jax
+    chex
+    flax
\ No newline at end of file

setup.py

+from setuptools import setup
+
+setup()

src/cyxtrax_object/__init__.py

+from .circular_trajectory import (
+    circular_trajectory,
+    add_world_orign,
+    add_offset,
+    add_origin,
+)
+from jax import numpy as jnp
+from jax.scipy.spatial.transform import Rotation
+from .object_placement import CircularTrajectoryOptimization
+from .plot_png import plot_map
+from .geometry_artist import set_geometry_at_index
+
+zero_quat = jnp.array([0.0, 0.0, 0.0, 1.0])
+
+z_90_quat = Rotation.from_euler("Z", 90.0, True).as_quat()
+y_90_quat = Rotation.from_euler("Y", 90.0, True).as_quat()
+x_90_quat = Rotation.from_euler("X", 90.0, True).as_quat()
+
+
+def x_deg2quat(x):
+    return Rotation.from_euler("X", x, True).as_quat()
+
+
+def y_deg2quat(x):
+    return Rotation.from_euler("Y", x, True).as_quat()
+
+
+def z_deg2quat(x):
+    return Rotation.from_euler("Z", x, True).as_quat()
+
+
+__all__ = [
+    "CircularTrajectoryOptimization",
+    "plot_map",
+    "set_geometry_at_index",
+    "add_origin",
+    "add_offset",
+    "add_world_orign",
+    "circular_trajectory",
+]

src/cyxtrax_object/circular_trajectory.py

+from jax import numpy as jnp, vmap, jit
+from jax.scipy.spatial.transform import Rotation
+import chex
+
+
+@jit
+def as_quat(rot: Rotation) -> jnp.ndarray:
+    return rot.as_quat()
+
+
+@jit
+def pose(pos: chex.Array, rot: chex.Array):
+    chex.assert_shape(pos, (3,))
+    chex.assert_shape(rot, (4,))
+
+    matrix = jnp.eye(4)
+    matrix = matrix.at[:3, :3].set(Rotation.from_quat(rot).as_matrix())
+    matrix = matrix.at[:3, 3].set(pos)
+    return matrix
+
+
+@jit
+def pose_inv_rot(pos: chex.Array, rot: chex.Array):
+    chex.assert_shape(pos, (3,))
+    chex.assert_shape(rot, (4,))
+
+    matrix = jnp.eye(4)
+    matrix = matrix.at[:3, :3].set(Rotation.from_quat(rot).as_matrix().T)
+    matrix = matrix.at[:3, 3].set(pos)
+    return matrix
+
+
+@jit
+def pos_quat(pose: chex.Array):
+    chex.assert_shape(pose, (4, 4))
+
+    return pose[:3, 3], Rotation.from_matrix(pose[:3, :3]).as_quat()
+
+
+@jit
+def circular_trajectory(fod_mm: chex.Array, fdd_mm: chex.Array, alpha_rad: chex.Array):
+    chex.assert_shape(fod_mm, (1,))
+    chex.assert_shape(fdd_mm, (1,))
+    chex.assert_rank(alpha_rad, 2)
+    chex.assert_axis_dimension(alpha_rad, 1, 1)
+
+    source = jnp.eye(4)
+    detector = jnp.eye(4)
+    detector = detector.at[2, 3].set(fod_mm[0])
+    source = source.at[2, 3].set((fod_mm - fdd_mm)[0])
+    rotations = Rotation.from_euler("y", alpha_rad, degrees=False)
+    rotations_negative = Rotation.from_euler("y", alpha_rad + jnp.pi, degrees=False)
+    source = rotations.apply(source[:3, 3])
+    detector = rotations.apply(detector[:3, 3])
+    orientation_source = vmap(as_quat)(rotations)
+    orientation_detector = vmap(as_quat)(rotations_negative)
+
+    return source, orientation_source, detector, orientation_detector
+
+
+@jit
+def add_origin(
+    input_position: chex.Array,
+    input_quat: chex.Array,
+    origin_position: chex.Array,
+    origin_quat: chex.Array,
+):
+    chex.assert_rank(input_position, 2)
+    chex.assert_rank(input_quat, 2)
+    chex.assert_rank(origin_position, 1)
+    chex.assert_rank(origin_quat, 1)
+    chex.assert_axis_dimension(input_position, 1, 3)
+    chex.assert_axis_dimension(input_quat, 1, 4)
+    chex.assert_axis_dimension(origin_position, 0, 3)
+    chex.assert_axis_dimension(origin_quat, 0, 4)
+
+    input_trafos = vmap(pose)(input_position, input_quat)
+    origin_trafo = pose(origin_position, origin_quat)
+    origin_trafo = jnp.expand_dims(origin_trafo, 0)
+
+    trafos = jnp.matmul(origin_trafo, input_trafos)
+    pos, ori = vmap(pos_quat)(trafos)
+    return pos, ori
+
+
+@jit
+def add_offset(
+    input_position: chex.Array,
+    input_quat: chex.Array,
+    origin_position: chex.Array,
+    origin_quat: chex.Array,
+):
+    chex.assert_rank(input_position, 2)
+    chex.assert_rank(input_quat, 2)
+    chex.assert_rank(origin_position, 1)
+    chex.assert_rank(origin_quat, 1)
+    chex.assert_axis_dimension(input_position, 1, 3)
+    chex.assert_axis_dimension(input_quat, 1, 4)
+    chex.assert_axis_dimension(origin_position, 0, 3)
+    chex.assert_axis_dimension(origin_quat, 0, 4)
+
+    input_trafos = vmap(pose)(input_position, input_quat)
+    origin_trafo = pose_inv_rot(origin_position, origin_quat)
+    origin_trafo = jnp.expand_dims(origin_trafo, 0)
+
+    trafos = jnp.matmul(input_trafos, origin_trafo)
+    pos, ori = vmap(pos_quat)(trafos)
+    return pos, ori
+
+
+@jit
+def add_world_orign(
+    source_position,
+    source_quat,
+    detector_position,
+    detector_quat,
+    origin_position,
+    origin_quat,
+):
+    source_position, source_quat = add_origin(
+        source_position, source_quat, origin_position, origin_quat
+    )
+    detector_position, detector_quat = add_origin(
+        detector_position, detector_quat, origin_position, origin_quat
+    )
+    return source_position, source_quat, detector_position, detector_quat

src/cyxtrax_object/geometry_artist.py

+try:
+    from artist_pythonlib import API, SAVEMODES  # type: ignore
+except ModuleNotFoundError:
+    from warnings import warn
+
+    warn(
+        "The module `artistlib`is not installed. The simulation module is not 100\% usable! \nInstall: https://github.com/wittlsn/aRTist-PythonLib"
+    )
+
+    def API():
+        return None
+
+    utility = None
+    SAVEMODES = None
+from pathlib import Path
+
+
+def set_geometry_at_index(
+    source,
+    orientation_source,
+    detector,
+    orientation_detector,
+    index,
+    temp_projection: Path = None,
+):
+    api = API()
+    api.translate("S", source[index, 0], source[index, 1], source[index, 2])
+    api.translate("D", detector[index, 0], detector[index, 1], detector[index, 2])
+    api.rotate_from_quat("D", orientation_detector[index])
+    api.rotate_from_quat("S", orientation_source[index])
+
+    if temp_projection is not None:
+        api.save_image(temp_projection, save_mode=SAVEMODES.FLOAT_TIFF)

src/cyxtrax_object/object_placement.py

+from flax import nnx
+from jax import numpy as jnp, vmap
+import chex
+from cyxtrax.mapping import map_source_2_cylinder
+from cyxtrax_object import circular_trajectory, add_world_orign
+from jax.scipy.spatial.transform import Rotation
+
+
+x_90_quat = Rotation.from_euler("X", 90.0, True).as_quat()
+
+
+class RayCalculator(nnx.Module):
+    def __init__(
+        self,
+        maps: chex.Array,
+        map_positions: chex.Array,
+        radius: float = 1000.0,
+        angle_discretisation: int = 2000,
+        pitch: float = jnp.pi,
+    ) -> None:
+        chex.assert_rank(maps, 3)
+        chex.assert_rank(map_positions, 2)
+        chex.assert_axis_dimension(map_positions, 0, 3)
+
+        self.maps = maps
+        self.map_positions = map_positions
+        self.radius = radius
+        self.angle_discretisation = angle_discretisation
+        self.pitch = pitch
+
+    def __call__(self, source_positions):
+        ray_values = vmap(map_source_2_cylinder, (0, None, None, None, None, None))(
+            source_positions,
+            self.maps,
+            self.map_positions,
+            self.radius,
+            self.angle_discretisation,
+            self.pitch,
+        )
+        return ray_values[0]
+
+
+class CircularTrajectoryOptimization(nnx.Module):
+    def __init__(
+        self,
+        maps,
+        map_positions,
+        radius: float = 1000,
+        angle_discretisation: int = 2000,
+        pitch: float = jnp.pi,
+        number_of_projection: int = 1000,
+        fod_mm: float = 1000,
+        fdd_mm: float = 2000.0,
+        gamma: float = jnp.pi * 2.0,
+        euler_conv: str = "YZ",
+        only_orientation: bool = False,
+    ) -> None:
+        self.ray_calc = RayCalculator(
+            maps, map_positions, radius, angle_discretisation, pitch
+        )
+
+        self.alpha_x_deg = nnx.Param(jnp.zeros((1, 1)))
+        self.beta_y_deg = nnx.Param(jnp.zeros((1, 1)))
+
+        if only_orientation:
+            self.origin = nnx.Variable(jnp.zeros((1, 3)))
+        else:
+            self.origin = nnx.Param(jnp.zeros((1, 3)))
+
+        self.number_of_projections = number_of_projection
+        self.fod_mm = jnp.array(fod_mm).reshape((1,))
+        self.fdd_mm = jnp.array(fdd_mm).reshape((1,))
+        self.gamma = gamma
+        self.euler_conv = euler_conv
+
+    def __call__(self):
+        source, orientation_source, detector, orientation_detector = (
+            self.get_state_trajectory()
+        )
+        return vmap(self.ray_calc)(source)
+
+    def get_trajectory(self):
+        alpha_rad = jnp.linspace(0, self.gamma, self.number_of_projections).reshape(
+            (-1, 1)
+        )
+        return add_world_orign(
+            *circular_trajectory(self.fod_mm, self.fdd_mm, alpha_rad),
+            jnp.zeros((3,)),
+            x_90_quat,
+        )
+
+    def get_state_trajectory(self):
+        source, orientation_source, detector, orientation_detector = (
+            self.get_trajectory()
+        )
+        angles = jnp.concatenate(
+            (self.alpha_x_deg.value, self.beta_y_deg.value), axis=-1
+        )
+        origin_quat = Rotation.from_euler(self.euler_conv, angles, True).as_quat()
+
+        return vmap(add_world_orign, in_axes=(None, None, None, None, 0, 0))(
+            source,
+            orientation_source,
+            detector,
+            orientation_detector,
+            jnp.array(self.origin),
+            origin_quat,
+        )

src/cyxtrax_object/plot_png.py

+from matplotlib import pyplot as plt
+from pathlib import Path
+
+
+def plot_map(map, angle_min: list, folder: Path, name: str):
+    fig = plt.figure(figsize=(10, 8))
+    ax = fig.add_subplot(111)
+    ax.imshow(map)
+    ax.set_xlabel(r"$\alpha$ / °")
+    ax.set_ylabel(r"$\beta$ / °")
+    ax.set_xticks([0, int(map.shape[0] // 2), int(map.shape[0]) - 1])
+    ax.set_xticklabels([f"-{angle_min[0]:2.2f}", "0.", f"{angle_min[0]:2.2f}"])
+    ax.set_yticks([0, int(map.shape[1] // 2), int(map.shape[1]) - 1])
+    ax.set_yticklabels([f"-{angle_min[1]:2.2f}", "0.", f"{angle_min[1]:2.2f}"])
+    ax.set_title(f"Map {name}")
+    name = name.replace(" ", "")
+    fig.savefig(folder / f"{name.lower()}_map.png")

temp/logo.svg

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+    <text
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+         dx="0">TWIN ROBOTIC CT</tspan></text>
+    <text
+       xml:space="preserve"
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