DiamondLightSource / Savu

from savu.plugins.utils import register_plugin

# this decorator is required for the configurator to recognise the plugin

@register_plugin

class PluginTemplate1WithDetailedNotes(Plugin, CpuPlugin):

# Each class must inherit from the Plugin class and a driver

    def __init__(self):

        super(PluginTemplate1WithDetailedNotes, self).__init__('PluginTemplate1WithDetailedNotes')

    def nInput_datasets(self):

        # Called immediately after the plugin is loaded in to the framework

        return 1

    def nOutput_datasets(self):

        # Called immediately after the plugin is loaded in to the framework

        return 1

    def setup(self):

        # This method is called after the number of in/out datasets associated

        # with the plugin has been established.  It tells the framework all

        # the information it needs to know about the data transport to-and-from

        # the plugin.

        #================== Input and output datasets =========================

        # in_datasets and out_datasets are instances of the Data class.

        # in_datasets were either created in the loader or as output from

        # previous plugins.  out_datasets objects have already been created at

        # this point, but they are empty and need to be populated.

        # Get the Data instances associated with this plugin

        in_dataset, out_dataset = self.get_datasets()

        # see https://savu.readthedocs.io/en/latest/api/savu.data.data_structures.data_create/

        # for more information on creating datasets.

        # Populate the output dataset(s)

        out_dataset[0].create_dataset(in_dataset[0])

        #================== Input and output plugin datasets ==================

        # in_pData and out_pData are instances of the PluginData class.

        # All in_datasets and out_datasets above have an in/out_pData object

        # attached to them temporarily for the duration of the plugin,

        # giving access to additional plugin-specific dataset details. At this

        # point they have been created but not yet populated.

        # Get the PluginData instances attached to the Data instances above

        in_pData, out_pData = self.get_plugin_datasets()

        # Each plugin dataset must call this method and define the data access

        # pattern and number of frames required.

        in_pData[0].plugin_data_setup('SINOGRAM', 'single')

        # 'single', 'multiple' or an int (should only be used if essential)

        out_pData[0].plugin_data_setup('SINOGRAM', 'single')

        # All dataset information can be accessed via the Data and PluginData

        # instances

    def pre_process(self):

        # This method is called once before any processing has begun.

        # Access parameters from the doc string in the parameters dictionary

        # e.g. self.parameters['example']

        pass

    def process_frames(self, data):

        # This function is called in a loop by the framework until all the

        # data has been processed.

        # Each iteration of the loop will receive a list of numpy arrays

        # (data) containing nInput_datasets with the data sliced as requested

        # in the setup method (SINOGRAM in this case).  If 'multiple' or an 

        # integer number of max_frames are requested the array with have an

        # extra dimension.

        # This plugin has one output dataset, so a single numpy array (a

        # SINOGRAM in this case) should be returned to the framework.

        return data[0]

    def post_process(self):

        # This method is called once after all processing has completed

        # (after an MPI barrier).

        pass

from savu.plugins.utils import register_plugin

@register_plugin

class PluginTemplate1(Plugin, CpuPlugin):

    def __init__(self):

        super(PluginTemplate1, self).__init__('PluginTemplate1')

    def nInput_datasets(self):

        return 1

    def nOutput_datasets(self):

        return 1

    def setup(self):

        in_dataset, out_dataset = self.get_datasets()

        out_dataset[0].create_dataset(in_dataset[0])

        in_pData, out_pData = self.get_plugin_datasets()

        in_pData[0].plugin_data_setup('SINOGRAM', 'single')

        out_pData[0].plugin_data_setup('SINOGRAM', 'single')

    def pre_process(self):

        pass

    def process_frames(self, data):

        # do some processing here

        # here is how to access a parameter defined in the tools file

        example = self.parameters['example']

        return data[0]*example

    def post_process(self):

        pass