Perform reconstruction of input tilt series.

Parameters:¶

stack: ndarray¶

NumPy array containing the input tilt series for a TomoStack

tilts: ndarray¶

The tilt angles for the tilt series (usually found in the TomoStack.tilts.data property). Should be a one-dimensional array, so it may be necessary to use the squeeze() method (e.g. tilts=stack.tilts.data.squeeze()).

method: 'FBP' | 'SIRT' | 'SART' | 'DART'¶

Reconstruction algorithm to use. Must be either ‘FBP’ (default), ‘SIRT’, ‘SART’, or ‘DART

niterations: int = 20¶

Number of iterations for reconstruction (used with SIRT, SART, and DART methods)

constrain: bool = False¶

If True, output reconstruction is constrained above value given by ‘thresh’

thresh: float = 0¶

Value above which to constrain the reconstructed data

cuda: bool | None = None¶

If True, use the CUDA-accelerated Astra algorithms. Otherwise, use the CPU-based algorithms

thickness: int | None = None¶

Limit for the height of the reconstruction. If None, the y-size of the stack is used.

ncores: int | None = None¶

Number of cores to use for multithreaded CPU-based reconstructions

bp_filter: 'ram-lak' | 'shepp-logan' | 'cosine' | 'hamming' | 'hann' | 'none' | 'tukey' | 'lanczos' | 'triangular' | 'gaussian' | 'barlett-hann' | 'blackman' | 'nuttall' | 'blackman-harris' | 'blackman-nuttall' | 'flat-top' | 'kaiser' | 'parzen' | 'projection' | 'sinogram' | 'rprojection' | 'rsinogram' = 'shepp-logan'¶

Filter to use for filtered backprojection

gray_levels: list | ndarray | None = None¶

Gray levels for DART reconstruction

dart_iterations: int = 2¶

Number of DART iterations

p: float = 0.99¶

Probability for setting free pixels in DART reconstruction

show_progressbar: bool = True¶

If True, show a progress bar for the reconstruction. Default is True.

Returns:¶

rec – Containing the reconstructed volume

Return type:¶

ndarray