Physical Object¶

class diffinytrace.physical_object.PhysicalObject[source]¶

Bases: Module

Abstract base class for physical objects in the optical system. This class can be used to define surface distance constraints and is also used for plotting.

get_transformation_matrix()[source]¶

Returns the transformation matrix of the object.

Returns:: The transformation matrix.
Return type:: torch.Tensor

to_global_dir(direction)[source]¶

Converts a direction vector from local to global coordinates.

Parameters:: direction (torch.Tensor) – Direction vector in local coordinates.
Returns:: Direction vector in global coordinates.
Return type:: torch.Tensor

to_local_dir(direction)[source]¶

Converts a direction vector from global to local coordinates.

Parameters:: direction (torch.Tensor) – Direction vector in global coordinates.
Returns:: Direction vector in local coordinates.
Return type:: torch.Tensor

to_global_pos(position)[source]¶

Converts a position from local to global coordinates.

Parameters:: position (torch.Tensor) – Position in local coordinates.
Returns:: Position in global coordinates.
Return type:: torch.Tensor

to_local_pos(position)[source]¶

Converts a position from global to local coordinates.

Parameters:: position (torch.Tensor) – Position in global coordinates.
Returns:: Position in local coordinates.
Return type:: torch.Tensor

get_transform()[source]¶

Returns the transformation object associated with this physical object.

Raises:: NotImplementedError – If not implemented in subclass.
Returns:: Transformation object.
Return type:: object

class diffinytrace.physical_object.PhysicalSurface[source]¶

Bases: PhysicalObject

Abstract base class for physical surfaces in the optical system. This class can be used to define surface distance constraints and is also used for plotting.

get_constraint_funs_leq_zero()[source]¶

Returns constraint functions for the surface that must be less than or equal to zero.

Raises:: NotImplementedError – If not implemented in subclass.
Returns:: List of constraint functions.
Return type:: list[Callable]

parametric_sample(num_points: int, method: str = 'sobol') → tuple[Tensor, Tensor][source]¶

Samples points on the surface in parameter space.

Parameters:

num_points (int) – Number of points to sample.
method (str, optional) – Sampling method. Defaults to “sobol”.

Raises:

NotImplementedError – If not implemented in subclass.

Returns:

Sampled parameter positions and corresponding surface positions.

Return type:

tuple[torch.Tensor, torch.Tensor]

parametric_surface(parametric_pos: Tensor) → Tensor[source]¶

Maps parameter space positions to surface positions.

Parameters:: parametric_pos (torch.Tensor) – Positions in parameter space.
Raises:: NotImplementedError – If not implemented in subclass.
Returns:: Surface positions.
Return type:: torch.Tensor