class VoCentering

executive_summary()

Provide a summary to the user for the result of the plugin.

e.g.

• Warning, the sample may have shifted during data collection

• Filter operated normally

Returns

A list of string summaries

fix_transport()

get_max_frames()

nOutput_datasets()

The number of datasets created by the plugin

Returns

Number of output datasets

populate_meta_data(key, value)

post_process()

This method is called after the process function in the pipeline framework as a post-processing step. All processes will have finished performing the main processing at this stage.

Parameters

exp (experiment class instance) – An experiment object, holding input and output datasets

pre_process()

This method is called immediately after base_pre_process().

process_frames(data)

This method is called after the plugin has been created by the pipeline framework and forms the main processing step

Parameters

data (list(np.array)) – A list of numpy arrays for each input dataset.

set_filter_padding(in_data, out_data)

Should be overridden to define how wide the frame should be for each input data set

setup()

This method is first to be called after the plugin has been created. It determines input/output datasets and plugin specific dataset information such as the pattern (e.g. sinogram/projection).