Source code for savu.data.transport_data.hdf5_transport_data

# Copyright 2014 Diamond Light Source Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""
.. module:: hdf5_transport_data
   :platform: Unix
   :synopsis: A data transport class that is inherited by Data class at \
   runtime. It organises the slice list and moves the data.

.. moduleauthor:: Nicola Wadeson <scientificsoftware@diamond.ac.uk>

"""

import os

from savu.data.transport_data.slice_lists import \
    SliceLists, GlobalData, LocalData
from savu.data.transport_data.base_transport_data import BaseTransportData


[docs]class Hdf5TransportData(BaseTransportData, SliceLists): """ The Hdf5TransportData class performs the organising and movement of data. """ def __init__(self, data_obj, name='Hdf5TransportData'): super(Hdf5TransportData, self).__init__(data_obj) self.mfp = None self.params = None if os.environ['savu_mode'] == 'basic': self.max_frames_function = self._calc_max_frames_transfer_single else: self.max_frames_function = self._calc_max_frames_transfer_multi def _get_slice_lists_per_process(self, dtype): pData = self.data._get_plugin_data() pData._set_padding_dict() self.pad = True if pData.padding else False self.transfer_data = GlobalData(dtype, self) trans_dict = self.transfer_data._get_dict(pData._plugin.fixed_length) proc_dict = LocalData(dtype, self)._get_dict() return self.__combine_dicts(trans_dict, proc_dict) def __combine_dicts(self, d1, d2): for key, value in d2.items(): d1[key] = value return d1 def _get_padded_data(self, slice_list, end=False): return self.transfer_data._get_padded_data(slice_list, end=False) def _calc_max_frames_transfer(self, nFrames): return self.max_frames_function(nFrames)