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# Copyright 2014 Diamond Light Source Ltd. |
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# |
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# Licensed under the Apache License, Version 2.0 (the "License"); |
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# you may not use this file except in compliance with the License. |
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# You may obtain a copy of the License at |
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# |
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# http://www.apache.org/licenses/LICENSE-2.0 |
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# |
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# Unless required by applicable law or agreed to in writing, software |
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# distributed under the License is distributed on an "AS IS" BASIS, |
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
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# See the License for the specific language governing permissions and |
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# limitations under the License. |
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# the information below is used in the auto-API creation for documentation |
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# and the synopsis appears in the configurator. |
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""" |
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.. module:: plugin_template1_with_detailed_notes |
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:platform: Unix |
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:synopsis: A template to create a simple plugin that takes one dataset as\ |
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input and returns a similar dataset as output. |
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.. moduleauthor:: Developer Name <[email protected]> |
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""" |
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from savu.plugins.plugin import Plugin |
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from savu.plugins.driver.cpu_plugin import CpuPlugin |
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from savu.plugins.utils import register_plugin |
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# this decorator is required for the configurator to recognise the plugin |
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View Code Duplication |
@register_plugin |
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class PluginTemplate1WithDetailedNotes(Plugin, CpuPlugin): |
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# Each class must inherit from the Plugin class and a driver |
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def __init__(self): |
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super(PluginTemplate1WithDetailedNotes, self).__init__('PluginTemplate1WithDetailedNotes') |
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def nInput_datasets(self): |
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# Called immediately after the plugin is loaded in to the framework |
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return 1 |
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def nOutput_datasets(self): |
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# Called immediately after the plugin is loaded in to the framework |
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return 1 |
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def setup(self): |
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# This method is called after the number of in/out datasets associated |
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# with the plugin has been established. It tells the framework all |
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# the information it needs to know about the data transport to-and-from |
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# the plugin. |
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#================== Input and output datasets ========================= |
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# in_datasets and out_datasets are instances of the Data class. |
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# in_datasets were either created in the loader or as output from |
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# previous plugins. out_datasets objects have already been created at |
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# this point, but they are empty and need to be populated. |
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# Get the Data instances associated with this plugin |
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in_dataset, out_dataset = self.get_datasets() |
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# see https://savu.readthedocs.io/en/latest/api/savu.data.data_structures.data_create/ |
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# for more information on creating datasets. |
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# Populate the output dataset(s) |
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out_dataset[0].create_dataset(in_dataset[0]) |
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#================== Input and output plugin datasets ================== |
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# in_pData and out_pData are instances of the PluginData class. |
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# All in_datasets and out_datasets above have an in/out_pData object |
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# attached to them temporarily for the duration of the plugin, |
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# giving access to additional plugin-specific dataset details. At this |
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# point they have been created but not yet populated. |
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# Get the PluginData instances attached to the Data instances above |
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in_pData, out_pData = self.get_plugin_datasets() |
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# Each plugin dataset must call this method and define the data access |
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# pattern and number of frames required. |
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in_pData[0].plugin_data_setup('SINOGRAM', 'single') |
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# 'single', 'multiple' or an int (should only be used if essential) |
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out_pData[0].plugin_data_setup('SINOGRAM', 'single') |
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# All dataset information can be accessed via the Data and PluginData |
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# instances |
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def pre_process(self): |
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# This method is called once before any processing has begun. |
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# Access parameters from the doc string in the parameters dictionary |
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# e.g. self.parameters['example'] |
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pass |
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def process_frames(self, data): |
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# This function is called in a loop by the framework until all the |
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# data has been processed. |
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# Each iteration of the loop will receive a list of numpy arrays |
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# (data) containing nInput_datasets with the data sliced as requested |
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# in the setup method (SINOGRAM in this case). If 'multiple' or an |
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# integer number of max_frames are requested the array with have an |
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# extra dimension. |
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# This plugin has one output dataset, so a single numpy array (a |
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# SINOGRAM in this case) should be returned to the framework. |
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return data[0] |
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def post_process(self): |
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# This method is called once after all processing has completed |
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# (after an MPI barrier). |
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pass |