class Plugin(name='Plugin')

base_post_process()

This method is called immediately after post_process().

base_pre_process()

This method is called after the plugin has been created by the pipeline framework as a pre-processing step.

base_process_frames_after(data)

This method is called directly after each call to process frames and before returning the data to file.

base_process_frames_before(data)

This method is called before each call to process frames

delete_parameter_entry(param)

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

final_parameter_updates()

An opportunity to update the parameters after they have been set.

get_current_slice_list()

Get the slice list of the current frame being processed.

get_global_frame_index()

Get the global frame index.

get_parameters(name)

Return a plugin parameter

Params str name

parameter name (dictionary key)

Returns

the associated value in self.parameters

Return type

dict value

get_plugin_tools()

get_process_frames_counter()

get_slice_dir_reps(nData)

Return the periodicity of the main slice direction.

Params int nData

The number of the dataset in the list.

initialise(params, exp, check=False)

nClone_datasets()

The number of output datasets that have an clone - i.e. they take it in turns to be used as output in an iterative plugin.

nFrames()

The number of frames to process during each call to process_frames.

nInput_datasets()

The number of datasets required as input to the plugin

Returns

Number of input datasets

nOutput_datasets()

The number of datasets created by the plugin

Returns

Number of output datasets

plugin_process_frames(data)

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_current_slice_list(sl)

set_filter_padding(in_data, out_data)

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

set_global_frame_index(frame_idx)

set_parameters(params)

set_preview(data, params)

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).