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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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""" |
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.. module:: testing_iterative_plugin |
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:platform: Unix |
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:synopsis: Iterative plugin example |
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.. moduleauthor:: Nicola Wadeson <[email protected]> |
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""" |
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import numpy as np |
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from savu.plugins.utils import register_plugin |
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from savu.plugins.filters.base_filter import BaseFilter |
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from savu.plugins.driver.iterative_plugin import IterativePlugin |
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@register_plugin |
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class TestingIterativePlugin(BaseFilter, IterativePlugin): |
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""" |
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A plugin to test the iterative plugin driver |
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:u*param nIterations: Number of iterations. Default: 10. |
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""" |
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def __init__(self): |
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super(TestingIterativePlugin, self).__init__("TestingIterativePlugin") |
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def pre_process(self): |
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self.set_iterations(self.parameters['nIterations']) |
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def process_frames(self, data): |
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# A random example function |
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if self.get_iteration() == 0: |
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return np.zeros(data[0].shape, dtype=np.float32) |
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return data[1] + np.ones(data[0].shape, dtype=np.float32)*10 |
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def post_process(self): |
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# option here to break out of the iterations |
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#self.set_processing_complete() |
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pass |
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View Code Duplication |
def setup(self): |
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# set up the output dataset that is created by the plugin |
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in_dataset, out_dataset = self.get_datasets() |
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in_pData, out_pData = self.get_plugin_datasets() |
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in_pData[0].plugin_data_setup('SINOGRAM', 'single') |
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# Cloned datasets are at the end of the out_dataset list |
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out_dataset[0].create_dataset(in_dataset[0]) |
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# What is a cloned dataset? |
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# Since each dataset in Savu has its own backing hdf5 file, a dataset |
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# cannot be used for input and output at the same time. So, in the |
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# case of iterative plugins, if a dataset is used as output and then |
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# as input on the next iteration, the subsequent output must be a |
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# different file. |
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# A cloned dataset is a copy of another dataset but with a different |
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# backing file. It doesn't have a name, is not accessible as a dataset |
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# in the framework and is only used in alternation with another |
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# dataset to allow it to be used as both input and output |
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# simultaneously. |
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# This is a cloned dataset (of out_dataset[0]) |
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self.create_clone(out_dataset[1], out_dataset[0]) |
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out_pData[0].plugin_data_setup('SINOGRAM', 'single') |
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out_pData[1].plugin_data_setup('SINOGRAM', 'single') |
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# input and output datasets for the first iteration |
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self.set_iteration_datasets(0, [in_dataset[0]], [out_dataset[0]]) |
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# input and output datasets for subsequent iterations |
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self.set_iteration_datasets(1, [in_dataset[0], out_dataset[0]], |
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[out_dataset[1]]) |
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# out_dataset[0] and out_dataset[1] will continue to alternate for |
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# all remaining iterations i.e. output becomes input and input becomes |
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# output. |
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# total number of output datasets |
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def nOutput_datasets(self): |
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return 2 |
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# total number of output datasets that are clones |
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def nClone_datasets(self): |
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return 1 |
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DiamondLightSource /
Savu
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