Optics#

class deeptrack.optical.optics.Optics(NA: float | Callable[[...], float] = 0.7, wavelength: float | Callable[[...], float] = 6.6e-07, magnification: float | Callable[[...], float] = 10, resolution: float | tuple[float, float] | tuple[float, float, float] | Callable[[...], float | tuple[float, float] | tuple[float, float, float]] = 1e-06, refractive_index_medium: float | Callable[[...], float] = 1.33, padding: tuple[int, int, int, int] | Callable[[...], tuple[int, int, int, int]] = (10, 10, 10, 10), output_region: tuple[int, int, int, int] | Callable[[...], tuple[int, int, int, int]] = (0, 0, 128, 128), pupil: Feature | None = None, illumination: Feature | None = None, upscale: int | tuple[int, int, int] | Callable[[...], int | tuple[int, int, int]] = 1, **kwargs: Any)#

Bases: Feature

Base class for optical systems.

Provides structure and methods common for most optical devices. Subclasses implement specific optical systems by defining imaging properties and behaviors. The Optics class is used to define the core imaging properties of an optical system, such as resolution, magnification, numerical aperture (NA), and wavelength.

Parameters#

NA: float, optional: Numerical aperture (NA) of the limiting aperture, by default 0.7.
wavelength: float, optional: Wavelength of the scattered light in meters, by default 0.66e-6.
magnification: float, optional: Magnification of the optical system, by default 10.
resolution: float or array_like[float], optional: Distance between pixels in the camera (meters). A third value can define the resolution in the z-direction, by default 1e-6.
refractive_index_medium: float, optional: Refractive index of the medium, by default 1.33.
padding: array_like[int, int, int, int], optional: Padding applied to the sample volume to avoid edge effects, by default (10, 10, 10, 10).
output_region: array_like[int, int, int, int], optional: Region of the image to output (x_min, y_min, x_max, y_max). If None, the entire image is returned, by default (0, 0, 128, 128).
pupil: Feature, optional: Feature-set resolving the pupil function at focus. By default, no pupil is applied.
illumination: Feature, optional: Feature-set resolving the illumination source. By default, no specific illumination is applied.
upscale: int or tuple[int, int, int], optional: Internal oversampling factor used during image formation. A scalar applies the same factor along all axes; a tuple specifies (ux, uy, uz). Larger values improve spatial sampling during propagation, after which the simulated image is downscaled back to detector resolution.
**kwargs: Any: Additional parameters passed to the base Feature class.

Attributes#

__conversion_table__: ConversionTable: Table used to convert properties of the feature to desired units.
NA: float: Numerical aperture of the optical system.
wavelength: float: Wavelength of the scattered light in meters.
refractive_index_medium: float: Refractive index of the medium.
magnification: float: Magnification of the optical system.
resolution: float or array_like[float]: Pixel spacing in the camera. Optionally includes the z-direction.
padding: array_like[int]: Padding applied to the sample volume to reduce edge effects.
output_region: array_like[int]: Region of the output image to extract (x_min, y_min, x_max, y_max).
voxel_size: function: Function returning the voxel size of the optical system.
pixel_size: function: Function returning the pixel size of the optical system.
upscale: int or tuple[int, int, int], optional: Internal oversampling factor used during image formation. A scalar applies the same factor along all axes; a tuple specifies (ux, uy, uz). Larger values improve spatial sampling during propagation, after which the simulated image is downscaled back to detector resolution.
limits: np.ndarray | torch.Tensor | None: Array of shape (3, 2) with volume bounds [[x_min, x_max], [y_min, y_max], [z_min, z_max]]. If None, bounds are initialized to zeros.
fields: list[Feature]: List of fields to be imaged.

Methods#

_process_properties(propertydict) -> dict[str, Any]: Processes and validates the input properties.
_pupil(…) -> array_like[complex]: Calculates the pupil function at different focal points.
_pad_volume(volume, limits, padding, output_region, **kwargs) -> tuple: Pads the volume with zeros to avoid edge effects.
__call__(sample: Feature, **kwargs: Any) -> Microscope: Creates a Microscope instance with the given sample and optics.

Examples#

Creating an Optics instance:

>>> import deeptrack as dt

>>> optics = dt.Optics(NA=0.8, wavelength=0.55e-6, magnification=20)
>>> print(optics.NA())
0.8

Methods Summary

__call__(sample, **kwargs)

Creates a Microscope instance with the given sample and optics.

Methods Documentation

__call__(sample: Feature, **kwargs: Any) → Microscope#

Creates a Microscope instance with the given sample and optics.

Parameters#

sample: Feature: The sample to be imaged.
**kwargs: Any: Additional parameters for the Microscope.

Returns#

Microscope: Microscope: A Microscope instance configured with the sample and optics.

Examples#

Creating a Microscope instance:

>>> import deeptrack as dt

>>> scatterer = dt.PointParticle()
>>> optics = dt.Optics()
>>> microscope = optics(scatterer)
>>> print(isinstance(microscope, dt.Microscope))
True