Rulings#

class optika.rulings.Rulings(spacing, diffraction_order)[source]#

Bases: AbstractRulings

An idealized set of rulings which have perfect efficiency in all diffraction orders.

Attributes

`diffraction_order`	The diffraction order to simulate.
`shape`	The array shape of this object.
`spacing`	Spacing between adjacent rulings at the given position.
`spacing_`	A normalized version of `spacing` that is guaranteed to be an instance of `optika.rulings.AbstractRulingSpacing`.

Methods

`__init__`(spacing, diffraction_order)
`efficiency`(rays, normal)	The fraction of light that is diffracted into a given order.
`incident_effective`(rays, normal)	Compute the effective propagation direction of the given rays using `incident_effective()`.
`to_string`([prefix])	Public-facing version of the `__repr__` method that allows for defining a prefix string, which can be used to calculate how much whitespace to add to the beginning of each line of the result.

Inheritance Diagram

Parameters:

spacing (Quantity | AbstractScalar | AbstractRulingSpacing)
diffraction_order (int | AbstractScalar)

efficiency(rays, normal)[source]#

The fraction of light that is diffracted into a given order.

Parameters:

rays (RayVectorArray) – The light rays incident on the rulings
normal (AbstractCartesian3dVectorArray) – The vector normal to the surface on which the rulings are placed.

Return type:

float

incident_effective(rays, normal)#

Compute the effective propagation direction of the given rays using incident_effective().

Parameters:

rays (RayVectorArray) – The light rays incident on the rulings
normal (AbstractCartesian3dVectorArray) – The vector normal to the surface on which the rulings are placed.

Return type:

RayVectorArray

to_string(prefix=None)#

Public-facing version of the __repr__ method that allows for defining a prefix string, which can be used to calculate how much whitespace to add to the beginning of each line of the result.

Parameters:: prefix (None | str) – an optional string, the length of which is used to calculate how much whitespace to add to the result.
Return type:: str

diffraction_order: int | AbstractScalar = <dataclasses._MISSING_TYPE object>#: The diffraction order to simulate.

property shape: dict[str, int]#: The array shape of this object.

spacing: Quantity | AbstractScalar | AbstractRulingSpacing = <dataclasses._MISSING_TYPE object>#: Spacing between adjacent rulings at the given position.

property spacing_: AbstractRulingSpacing#: A normalized version of spacing that is guaranteed to be an instance of optika.rulings.AbstractRulingSpacing.