class TomobarRecon

get_max_frames()

Number of data frames to pass to each instance of process_frames func

Returns

“single”, “multiple” or integer (only to be used if the number of

frames MUST be fixed.)

Return type

str or int

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

pre_process()

# current parameters not fully working yet :param data_any_rings: a parameter to suppress various artifacts including rings and streaks. Default: None. :param data_any_rings_winsizes: half window sizes to collect background information [detector, angles, num of projections]. Default: (9,7,0). :param data_any_rings_power: a power parameter for Huber model. Default: 1.5. ‘ring_weights_threshold’ : self.parameters[‘data_any_rings’], ‘ring_tuple_halfsizes’ : self.parameters[‘data_any_rings_winsizes’], ‘ring_huber_power’ : self.parameters[‘data_any_rings_power’],

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.