recon_loop

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recon_loop#

ptyrad.reconstruction.recon_loop(model, init, params, optimizer, loss_fn, constraint_fn, indices, batches, output_path, acc=None)[source]#

Executes the iterative optimization loop for ptychographic reconstruction.

This function performs the iterative reconstruction process by optimizing the model parameters over a specified number of iterations. During each iteration, it applies the loss and constraint functions, updates the model, and logs the loss values. Intermediate results are saved at specified intervals, and a summary is plotted.

Parameters:

  • model (PtychoAD) – The ptychographic model containing the parameters and variables to be optimized.

  • init (Initializer) – The initializer object containing the initialized variables needed for reconstruction.

  • params (dict) – A dictionary containing various parameters for the reconstruction process, including experimental parameters, source parameters, loss parameters, constraint parameters, and reconstruction settings.

  • optimizer (torch.optim.Optimizer) – The optimizer used to update the model parameters.

  • loss_fn (CombinedLoss) – The loss function object used to compute the loss during each iteration.

  • constraint_fn (CombinedConstraint) – The constraint function object applied during each iteration to enforce specific constraints on the model.

  • indices (numpy.ndarray) – Array of indices for scanning positions.

  • batches (list of numpy.ndarray) – List of batches where each batch contains indices grouped according to the selected grouping mode.

  • output_path (str) – The path to the directory where reconstruction results and figures will be saved.

Returns:

A list of tuples, where each tuple contains the iteration number, the loss

value for that iteration, and the time taken for that iteration.

Return type:

list

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