deeptrack.optical.holography Module

Core features for manipulating optical fields using Fourier transforms and propagation matrices.

This module includes operations to simulate optical field propagation and perform transformations in the frequency domain. These features can be combined in processing pipelines for optical simulations and holographic reconstructions.

Key Features

• Optical Field Processing

  Provides Fourier transforms, rescaling, and wavefront propagation for complex-valued optical fields, handling both real and imaginary components.

• Fourier Optics and Wave Propagation

  Implements Fourier transforms with optional padding for accurate frequency-domain analysis and propagation matrices to simulate free-space wavefront propagation with spatial and frequency domain shifts.

• Phase & Amplitude Manipulation

  Enables scaling, normalization, and modulation of phase and amplitude to preserve intensity distribution and enhance wavefront reconstruction.

• Backend Compatibility

  get_propagation_matrix supports both NumPy and PyTorch arrays via deeptrack.backend.xp. The Rescale, FourierTransform, InverseFourierTransform, and FourierTransformTransformation features currently operate on NumPy arrays only.

Module Structure

Classes:

• Rescale: Rescales an optical field by subtracting the real part of the

  field before multiplication.

• FourierTransform: Creates matrices for propagating an optical field.

• InverseFourierTransform: Creates matrices for propagating an optical field.

• FourierTransformTransformation: Applies a power of the forward or inverse

  propagation matrix to an optical field.

Functions:

• get_propagation_matrix(shape, to_z, pixel_size, wavelength, dx=0, dy=0)

  Computes the propagation matrix for simulating the propagation of an optical field.

Examples

Simulate optical field propagation with Fourier transforms:

>>> import deeptrack as dt
>>> import numpy as np

Define a random optical field: >>> field = np.random.rand(128, 128, 2)

Rescale the field and compute the Fourier transform: >>> rescale_op = dt.holography.Rescale(0.5) >>> scaled_field = rescale_op(field) >>> ft_op = dt.holography.FourierTransform() >>> transformed_field = ft_op(scaled_field)

Reconstruct the field using the inverse Fourier transform: >>> ift_op = dt.holography.InverseFourierTransform() >>> reconstructed_field = ift_op(transformed_field)

Functions

get_active_voxel_size()	Get the active voxel size used for simulation, in meters.
get_propagation_matrix(shape, to_z, ...[, ...])	Computes the propagation matrix for simulating the propagation of an optical field.

Classes

Feature([_input])	Base feature class.
FourierTransform(**kwargs)	Computes the Fourier transform of an optical field with optional symmetric padding.
FourierTransformTransformation(Tz, Tzinv, i, ...)	Applies a power of the forward or inverse propagation matrix to an optical field.
InverseFourierTransform(**kwargs)	Computes the inverse Fourier transform of an optical field and removes padding.
Rescale([rescale])	Rescales an optical field by modifying its real and imaginary components.