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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:: comparison  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                   :platform: Unix  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                   :synopsis: A plugin to compare two datasets, given as input datasets, and print the RMSD between the two.  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                              The data is unchanged.  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                .. moduleauthor:: Jacob Williamson <[email protected]>  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                """  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                from savu.plugins.utils import register_plugin  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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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.core.iterate_plugin_group_utils import enable_iterative_loop, \  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    check_if_end_plugin_in_iterate_group, setup_extra_plugin_data_padding  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                import os  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                import h5py as h5  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                # This decorator is required for the configurator to recognise the plugin  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                @register_plugin  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                class GatherStats(Plugin, CpuPlugin):  | 
            
            
                                                                                                            
                                                                
            
                                    
            
            
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                    def __init__(self):  | 
            
            
                                                                        
                            
            
                                    
            
            
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                        super(GatherStats, self).__init__("GatherStats") | 
            
            
                                                                                                            
                            
            
                                    
            
            
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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 0  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    def nClone_datasets(self):  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        if check_if_end_plugin_in_iterate_group(self.exp):  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                            return 1  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        else:  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                            return 0  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    @enable_iterative_loop  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    def setup(self):  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        in_dataset, out_dataset = self.get_datasets()  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        self.stats_obj.calc_stats = False  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        self.stats_obj.set_stats_key(["max", "min", "mean", "mean_std_dev", "median_std_dev", "zeros", "zeros%",  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                                                       "range_used"])  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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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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                        for i in range(len(in_pData)):  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                            in_pData[i].plugin_data_setup(self.parameters['pattern'], '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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                        in_datasets = self.get_in_datasets()  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    def process_frames(self, data):  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        self.stats_obj.set_slice_stats(data, pad=False)  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        return None  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    def post_process(self):  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        slice_stats = self.stats_obj.stats  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        comm = self.get_communicator()  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        combined_stats = self.stats_obj._combine_mpi_stats(slice_stats, comm=comm)  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        volume_stats = self.stats_obj.calc_volume_stats(combined_stats)  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        if self.exp.meta_data.get("pre_run"): | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                            self._generate_warnings(volume_stats)  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                            self.exp.meta_data.set("pre_run_stats", volume_stats) | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                            folder = self.exp.meta_data['out_path']  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                            fname = self.exp.meta_data.get('datafile_name') + '_pre_run.nxs' | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                            filename = os.path.join(folder, fname)  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                            stats_array = self.stats_obj._dict_to_array(volume_stats)  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                            if comm.rank == 0:  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                                with h5.File(filename, "a") as h5file:  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                                    fsplit = self.exp.meta_data["data_path"].split("/") | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                                    fsplit[-1] = ""  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                                    stats_path = "/".join(fsplit)  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                                    stats_group = h5file.require_group(stats_path)  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                                    dataset = stats_group.create_dataset("stats", shape=stats_array.shape, dtype=stats_array.dtype) | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                                    dataset[::] = stats_array[::]  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                                    dataset.attrs.create("stats_key", list(self.stats_obj.stats_key)) | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    def _generate_warnings(self, volume_stats):  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        warnings = []  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        if volume_stats["zeros%"] > 10:  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                            warnings.append(f"Percentage of data points that are 0s is {volume_stats['zeros%']}") | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        if volume_stats["range_used"] < 2:  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                            warnings.append(f"Only {volume_stats['range_used']}% of the possible range of the datatype (\ | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    113
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                {self.stats_obj.stats['dtype']}) has been used. The datatype used, {self.stats_obj.stats['dtype']} can go from \ | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    114
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                {self.stats_obj.stats['possible_min']} to {self.stats_obj.stats['possible_max']}") | 
            
            
                                                                                                            
                                                                
            
                                    
            
            
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                        self.exp.meta_data.set("warnings", warnings) | 
            
            
                                                        
            
                                    
            
            
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