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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:: sum_dimension  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                   :platform: Unix  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                   :synopsis: Sum a chosen dimension of the data.  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                .. moduleauthor:: Nicola Wadeson <[email protected]>  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                """  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                import copy  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                import logging  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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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.utils import register_plugin  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                from savu.plugins.driver.cpu_plugin import CpuPlugin  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                @register_plugin  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                class SumDimension(Plugin, CpuPlugin):  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    def __init__(self):  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        super(SumDimension, self).__init__('SumDimension') | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    def pre_process(self):  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        in_pData = self.get_plugin_in_datasets()[0]  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        self.sum_dim = in_pData.get_data_dimension_by_axis_label(  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                                self.parameters['axis_label'])  | 
            
            
                                                                                                            
                                                                
            
                                    
            
            
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                    def process_frames(self, data):  | 
            
            
                                                                        
                            
            
                                    
            
            
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                        return np.sum(data[0], axis=self.sum_dim)  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    def setup(self):  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        in_dataset, out_dataset = self.get_datasets()  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        rm_label = self.parameters['axis_label']  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        rm_dim = in_dataset[0].get_data_dimension_by_axis_label(rm_label)  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        patterns = ['*.' + str(rm_dim)]      | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        axis_labels = copy.copy(in_dataset[0].get_axis_labels())  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        del axis_labels[rm_dim]  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        shape = list(in_dataset[0].get_shape())  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        del shape[rm_dim]  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        out_dataset[0].create_dataset(  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                                patterns={in_dataset[0]: patterns}, | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                                axis_labels=axis_labels,  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                                shape=tuple(shape))  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        pattern = self.parameters['pattern']  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        in_pData, out_pData = self.get_plugin_datasets()  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        in_pData[0].plugin_data_setup(pattern, 'multiple')  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        out_pData[0].plugin_data_setup(pattern, 'multiple')  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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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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