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class
TomobarReconCpu
[source] -
get_max_frames
()[source] 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
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nInput_datasets
()[source] The number of datasets required as input to the plugin
- Returns
Number of input datasets
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nOutput_datasets
()[source] The number of datasets created by the plugin
- Returns
Number of output datasets
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pre_process
()[source] # 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’],
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process_frames
(data)[source] 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.
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