pyAPIC package

pyAPIC public API.

class pyAPIC.Case(data: ImagingData, params: ReconParams, _result: dict | None = None)

Bases: object

Encapsulates a reconstruction case: data, parameters, and results.

data: ImagingData

classmethod from_mat(mat_path: str, params: ReconParams, downsample: int = 1) → Case

Create a Case by loading imaging data from a .mat file and assigning parameters.

Parameters:

• mat_path (str) – Path to the .mat file (HDF5 based).

• params (ReconParams) – Reconstruction parameters.

• downsample (int) – Factor to subsample the LED stack.

Returns:

Initialized Case object (results empty until run()).

Return type:

Case

params: ReconParams

plot()

Generate result plot for this case.

plot_E_stack(ncols: int = 5) → None

Plot the LED stack as a grid of images.

Parameters:

ncols (int) – Number of columns in the grid.

plot_input(ncols: int = 5) → None

Plot the initial intensity stack as a grid of images.

Parameters:

ncols (int) – Number of columns in the grid.

property result: dict

Retrieve reconstruction outputs. Raises if run() has not been called.

run() → None

Execute the reconstruction algorithm. Populates self._result.

save(path: str) → None

Save the result dict to disk (e.g., pickle or HDF5).

Parameters:

path (str) – File path to save results.

class pyAPIC.ImagingData(I_low: ndarray, illum_px: ndarray, system_na_px: float, pixel_size: float | None = None, magnification: float | None = None, illum_na: ndarray | None = None, system_na: float | None = None, wavelength: float | None = None)

Bases: object

Container for imaging data and acquisition parameters.

I_low: ndarray

property dpix_c: float | None

property freqXY_calib: ndarray

illum_na: ndarray | None = None

illum_px: ndarray

property mag: float | None

magnification: float | None = None

property na_cal: float | None

property na_calib: ndarray | None

property na_rp_cal: float

pixel_size: float | None = None

system_na: float | None = None

system_na_px: float

wavelength: float | None = None

class pyAPIC.ReconParams(reconstruct_aberration: bool = False, stitch_method: str = 'average')

Bases: object

Parameters for phase reconstruction.

reconstruct_aberration

Whether to perform aberration reconstruction.

Type:

bool

stitch_method

Method used to stitch the Fourier patches (“average” or “nearest”).

Type:

str

reconstruct_aberration: bool = False

stitch_method: str = 'average'

pyAPIC.load_mat(path: str, downsample: int = 1) → ImagingData

Load imaging data and calibration parameters from a MATLAB .mat file (v7.3/HDF5).

Parameters:

• path (str) – Path to the .mat file.

• downsample (int) – Factor by which to subsample the image stack along the illumination axis.

Returns:

Populated dataclass.

Return type:

ImagingData

pyAPIC.to_pixel_coords(angles: ndarray, *, system_na_px: float, system_na: float | None = None, center: ndarray, wavelength: float | None = None, units: str = 'na', na_cal: float | None = None) → ndarray

Convert illumination angles to the illum_px pixel coordinates.

Parameters:

• angles – Array of illumination angles of shape (2, N).

• system_na_px – System numerical aperture expressed in pixel units.

• system_na – System numerical aperture (unitless). na_cal may be used as an alias for backward compatibility.

• center – Image center (y, x).

• wavelength – Illumination wavelength. Required when units='na'.

• units – Either 'na' for n sin(    heta) or 'freq' for spatial frequency units.