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# -*- coding: utf-8 -*- |
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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:: experiment |
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:platform: Unix |
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:synopsis: Contains information specific to the entire experiment. |
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.. moduleauthor:: Nicola Wadeson <[email protected]> |
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""" |
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import os |
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import copy |
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import h5py |
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import logging |
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from mpi4py import MPI |
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from savu.data.meta_data import MetaData |
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from savu.data.plugin_list import PluginList |
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from savu.data.data_structures.data import Data |
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from savu.core.checkpointing import Checkpointing |
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from savu.plugins.savers.utils.hdf5_utils import Hdf5Utils |
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import savu.plugins.loaders.utils.yaml_utils as yaml |
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class Experiment(object): |
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""" |
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One instance of this class is created at the beginning of the |
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processing chain and remains until the end. It holds the current data |
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object and a dictionary containing all metadata. |
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""" |
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def __init__(self, options): |
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self.meta_data = MetaData(options) |
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self.__set_system_params() |
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self.checkpoint = Checkpointing(self) |
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self.__meta_data_setup(options["process_file"]) |
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self.collection = {} |
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self.index = {"in_data": {}, "out_data": {}} |
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self.initial_datasets = None |
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self.plugin = None |
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self._transport = None |
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self._barrier_count = 0 |
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self._dataset_names_complete = False |
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def get(self, entry): |
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""" Get the meta data dictionary. """ |
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return self.meta_data.get(entry) |
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def __meta_data_setup(self, process_file): |
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self.meta_data.plugin_list = PluginList() |
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try: |
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rtype = self.meta_data.get('run_type') |
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if rtype == 'test': |
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self.meta_data.plugin_list.plugin_list = \ |
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self.meta_data.get('plugin_list') |
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else: |
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raise Exception('the run_type is unknown in Experiment class') |
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except KeyError: |
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template = self.meta_data.get('template') |
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self.meta_data.plugin_list._populate_plugin_list(process_file, |
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template=template) |
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self.meta_data.set("nPlugin", 0) # initialise |
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def create_data_object(self, dtype, name, override=True): |
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""" Create a data object. |
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Plugin developers should apply this method in loaders only. |
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:params str dtype: either "in_data" or "out_data". |
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""" |
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if name not in list(self.index[dtype].keys()) or override: |
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self.index[dtype][name] = Data(name, self) |
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data_obj = self.index[dtype][name] |
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data_obj._set_transport_data(self.meta_data.get('transport')) |
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return self.index[dtype][name] |
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def _setup(self, transport): |
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self._set_nxs_file() |
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self._set_process_list_path() |
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self._set_transport(transport) |
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self.collection = {'plugin_dict': [], 'datasets': []} |
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self._barrier() |
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self._check_checkpoint() |
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self._barrier() |
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def _finalise_setup(self, plugin_list): |
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checkpoint = self.meta_data.get('checkpoint') |
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self._set_dataset_names_complete() |
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# save the plugin list - one process, first time only |
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if self.meta_data.get('process') == \ |
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len(self.meta_data.get('processes'))-1 and not checkpoint: |
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# Save original process list |
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plugin_list._save_plugin_list(self.meta_data.get('process_list_path')) |
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# links the input data to the nexus file |
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plugin_list._save_plugin_list(self.meta_data.get('nxs_filename'), |
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self.meta_data.get('command')) |
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self._add_input_data_to_nxs_file(self._get_transport()) |
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self._set_dataset_names_complete() |
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def _set_initial_datasets(self): |
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self.initial_datasets = copy.deepcopy(self.index['in_data']) |
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def _set_transport(self, transport): |
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self._transport = transport |
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def _get_transport(self): |
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return self._transport |
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def __set_system_params(self): |
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sys_file = self.meta_data.get('system_params') |
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import sys |
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if sys_file is None: |
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# look in conda environment to see which version is being used |
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savu_path = sys.modules['savu'].__path__[0] |
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sys_files = os.path.join( |
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os.path.dirname(savu_path), 'system_files') |
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subdirs = os.listdir(sys_files) |
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sys_folder = 'dls' if len(subdirs) > 1 else subdirs[0] |
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fname = 'system_parameters.yml' |
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sys_file = os.path.join(sys_files, sys_folder, fname) |
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logging.info('Using the system parameters file: %s', sys_file) |
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self.meta_data.set('system_params', yaml.read_yaml(sys_file)) |
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def _check_checkpoint(self): |
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# if checkpointing has been set but the nxs file doesn't contain an |
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# entry then remove checkpointing (as the previous run didn't get far |
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# enough to require it). |
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if self.meta_data.get('checkpoint'): |
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with h5py.File(self.meta_data.get('nxs_filename'), 'r') as f: |
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if 'entry' not in f: |
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self.meta_data.set('checkpoint', None) |
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def _add_input_data_to_nxs_file(self, transport): |
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# save the loaded data to file |
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h5 = Hdf5Utils(self) |
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for name, data in self.index['in_data'].items(): |
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self.meta_data.set(['link_type', name], 'input_data') |
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self.meta_data.set(['group_name', name], name) |
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self.meta_data.set(['filename', name], data.backing_file) |
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transport._populate_nexus_file(data) |
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h5._link_datafile_to_nexus_file(data) |
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def _set_dataset_names_complete(self): |
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""" Missing in/out_datasets fields have been populated |
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""" |
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self._dataset_names_complete = True |
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def _get_dataset_names_complete(self): |
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return self._dataset_names_complete |
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def _reset_datasets(self): |
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self.index['in_data'] = self.initial_datasets |
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# clear out dataset dictionaries |
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for data_dict in self.collection['datasets']: |
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for data in data_dict.values(): |
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data.meta_data._set_dictionary({}) |
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def _get_collection(self): |
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return self.collection |
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def _set_experiment_for_current_plugin(self, count): |
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datasets_list = self.meta_data.plugin_list._get_datasets_list()[count:] |
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exp_coll = self._get_collection() |
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self.index['out_data'] = exp_coll['datasets'][count] |
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if datasets_list: |
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self._get_current_and_next_patterns(datasets_list) |
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self.meta_data.set('nPlugin', count) |
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def _get_current_and_next_patterns(self, datasets_lists): |
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""" Get the current and next patterns associated with a dataset |
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throughout the processing chain. |
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""" |
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current_datasets = datasets_lists[0] |
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patterns_list = {} |
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for current_data in current_datasets['out_datasets']: |
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current_name = current_data['name'] |
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current_pattern = current_data['pattern'] |
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next_pattern = self.__find_next_pattern(datasets_lists[1:], |
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current_name) |
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patterns_list[current_name] = \ |
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{'current': current_pattern, 'next': next_pattern} |
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self.meta_data.set('current_and_next', patterns_list) |
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def __find_next_pattern(self, datasets_lists, current_name): |
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next_pattern = [] |
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for next_data_list in datasets_lists: |
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for next_data in next_data_list['in_datasets']: |
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if next_data['name'] == current_name: |
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next_pattern = next_data['pattern'] |
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return next_pattern |
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return next_pattern |
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def _set_process_list_path(self): |
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"""Create the path the process list should be saved to""" |
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folder = self.meta_data.get('out_path') |
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plname = os.path.basename(self.meta_data.get('process_file')) |
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filename = os.path.join(folder, plname if plname |
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else "process_list.nxs") |
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self.meta_data.set('process_list_path', filename) |
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self._update_command() |
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def _update_command(self): |
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"""Update the input command and replace the path to the |
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process list""" |
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pl_path = self.meta_data.get('process_file') |
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new_pl_path = self.meta_data.get('process_list_path') |
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input_command = self.meta_data.get('command') |
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updated_command = input_command.replace(pl_path, new_pl_path) |
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self.meta_data.set('command', updated_command) |
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def _set_nxs_file(self): |
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folder = self.meta_data.get('out_path') |
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fname = self.meta_data.get('datafile_name') + '_processed.nxs' |
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filename = os.path.join(folder, fname) |
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self.meta_data.set('nxs_filename', filename) |
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if self.meta_data.get('process') == 1: |
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if self.meta_data.get('bllog'): |
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log_folder_name = self.meta_data.get('bllog') |
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with open(log_folder_name, 'a') as log_folder: |
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log_folder.write(os.path.abspath(filename) + '\n') |
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self._create_nxs_entry() |
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def _create_nxs_entry(self): # what if the file already exists?! |
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logging.debug("Testing nexus file") |
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if self.meta_data.get('process') == len( |
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self.meta_data.get('processes')) - 1 and not self.checkpoint: |
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with h5py.File(self.meta_data.get('nxs_filename'), 'w') as nxs_file: |
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entry_group = nxs_file.create_group('entry') |
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entry_group.attrs['NX_class'] = 'NXentry' |
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def _clear_data_objects(self): |
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self.index["out_data"] = {} |
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self.index["in_data"] = {} |
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def _merge_out_data_to_in(self, plugin_dict): |
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out_data = self.index['out_data'].copy() |
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for key, data in out_data.items(): |
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if data.remove is False: |
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self.index['in_data'][key] = data |
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self.collection['datasets'].append(out_data) |
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self.collection['plugin_dict'].append(plugin_dict) |
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self.index["out_data"] = {} |
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def _finalise_experiment_for_current_plugin(self): |
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finalise = {'remove': [], 'keep': []} |
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# populate nexus file with out_dataset information and determine which |
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# datasets to remove from the framework. |
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for key, data in self.index['out_data'].items(): |
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if data.remove is True: |
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finalise['remove'].append(data) |
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else: |
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finalise['keep'].append(data) |
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# find in datasets to replace |
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finalise['replace'] = [] |
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for out_name in list(self.index['out_data'].keys()): |
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if out_name in list(self.index['in_data'].keys()): |
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finalise['replace'].append(self.index['in_data'][out_name]) |
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return finalise |
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def _reorganise_datasets(self, finalise): |
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# unreplicate replicated in_datasets |
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self.__unreplicate_data() |
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# delete all datasets for removal |
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for data in finalise['remove']: |
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del self.index["out_data"][data.data_info.get('name')] |
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# Add remaining output datasets to input datasets |
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for name, data in self.index['out_data'].items(): |
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data.get_preview().set_preview([]) |
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self.index["in_data"][name] = copy.deepcopy(data) |
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self.index['out_data'] = {} |
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def __unreplicate_data(self): |
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|
|
in_data_list = self.index['in_data'] |
|
296
|
|
|
from savu.data.data_structures.data_types.replicate import Replicate |
|
297
|
|
|
for in_data in list(in_data_list.values()): |
|
298
|
|
|
if isinstance(in_data.data, Replicate): |
|
299
|
|
|
in_data.data = in_data.data._reset() |
|
300
|
|
|
|
|
301
|
|
|
def _set_all_datasets(self, name): |
|
302
|
|
|
data_names = [] |
|
303
|
|
|
for key in list(self.index["in_data"].keys()): |
|
304
|
|
|
if 'itr_clone' not in key: |
|
305
|
|
|
data_names.append(key) |
|
306
|
|
|
return data_names |
|
307
|
|
|
|
|
308
|
|
|
def _barrier(self, communicator=MPI.COMM_WORLD, msg=''): |
|
309
|
|
|
comm_dict = {'comm': communicator} |
|
310
|
|
|
if self.meta_data.get('mpi') is True: |
|
311
|
|
|
logging.debug("Barrier %d: %d processes expected: %s", |
|
312
|
|
|
self._barrier_count, communicator.size, msg) |
|
313
|
|
|
comm_dict['comm'].barrier() |
|
314
|
|
|
self._barrier_count += 1 |
|
315
|
|
|
|
|
316
|
|
|
def log(self, log_tag, log_level=logging.DEBUG): |
|
317
|
|
|
""" |
|
318
|
|
|
Log the contents of the experiment at the specified level |
|
319
|
|
|
""" |
|
320
|
|
|
logging.log(log_level, "Experimental Parameters for %s", log_tag) |
|
321
|
|
|
for key, value in self.index["in_data"].items(): |
|
322
|
|
|
logging.log(log_level, "in data (%s) shape = %s", key, |
|
323
|
|
|
value.get_shape()) |
|
324
|
|
|
for key, value in self.index["in_data"].items(): |
|
325
|
|
|
logging.log(log_level, "out data (%s) shape = %s", key, |
|
326
|
|
|
value.get_shape()) |
|
327
|
|
|
|
DiamondLightSource /
Savu
