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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:: plugin_template6 |
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:platform: Unix |
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:synopsis: A template to create a plugin that changes the shape of the data. |
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.. moduleauthor:: Developer Name <[email protected]> |
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""" |
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import numpy as np |
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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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@register_plugin |
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class PluginTemplate6(Plugin, CpuPlugin): |
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def __init__(self): |
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super(PluginTemplate6, self).__init__('PluginTemplate6') |
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def nInput_datasets(self): |
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return 1 |
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def nOutput_datasets(self): |
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return 1 |
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def setup(self): |
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# get all in and out datasets required by the plugin |
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in_dataset, self.out_dataset = self.get_datasets() |
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# set in_plugin_dataset first so pattern information is available to |
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# calculate the new shape |
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self.in_pData, self.out_pData = self.get_plugin_datasets() |
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pattern = self.parameters['pattern'] |
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self.in_pData[0].plugin_data_setup(pattern, 'single') |
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# calculate the output shape (based on the input shape) |
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self.out_shape = \ |
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self.new_shape(in_dataset[0].get_shape(), in_dataset[0]) |
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#=================== populate output datasets ========================= |
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# the output data shape retains the same patterns and axis labels but |
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# requires a different shape. |
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self.out_dataset[0].create_dataset(patterns=in_dataset[0], |
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axis_labels=in_dataset[0], |
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shape=self.out_shape) |
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#================== populate output plugin datasets =================== |
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self.out_pData[0].plugin_data_setup(pattern, 'single') |
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def new_shape(self, full_shape, data): |
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# example of a function to calculate a new output data shape based on |
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# the input data shape |
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core_dirs = data.get_core_dimensions() |
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new_shape = list(full_shape) |
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for dim in core_dirs: |
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new_shape[dim] = full_shape[dim] // self.parameters['bin_size'] |
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return tuple(new_shape) |
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def pre_process(self): |
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# Example of calculating a new slice list to reduce the data |
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in_data_shape = self.in_pData[0].get_shape() |
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bin_size = self.parameters['bin_size'] |
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new_sl = [slice(0, i, bin_size) for i in in_data_shape] |
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# update all axis label values based on the new slice list |
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self.out_dataset[0].amend_axis_label_values( |
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self.out_pData[0]._get_data_slice_list(new_sl)) |
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def process_frames(self, data): |
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# replace this with your function |
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return np.zeros(self.get_plugin_out_datasets()[0].get_shape()) |
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def post_process(self): |
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pass |
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