# 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:: tomophantom_loader
:platform: Unix
:synopsis: A full-field tomography loader that creates a NeXus file in \
NXtomo format and contains tomographic synthetic data generated hdf5 dataset of a \
specified size.
.. moduleauthor:: Daniil Kazantsev <scientificsoftware@diamond.ac.uk>
"""
import numpy as np
from savu.plugins.utils import register_plugin
from savu.plugins.loaders.base_tomophantom_loader import BaseTomophantomLoader
from savu.data.data_structures.data_types.data_plus_darks_and_flats \
import ImageKey
[docs]@register_plugin
class TomoPhantomLoader(BaseTomophantomLoader):
def __init__(self, name='TomoPhantomLoader'):
super(TomoPhantomLoader, self).__init__(name)
[docs] def setup(self):
data_obj,data_obj2 = super(TomoPhantomLoader, self).setup()
image_key = self.__set_image_key(data_obj)
data_obj.data = ImageKey(data_obj, image_key, 0)
data_obj.set_shape(data_obj.data.shape)
self.set_data_reduction_params(data_obj)
data_obj2.set_shape(data_obj2.data.shape)
self.set_data_reduction_params(data_obj2)
super(TomoPhantomLoader, self).post_process(data_obj, data_obj2)
self.proj_stats_obj.stop_time()
def __set_image_key(self, data_obj):
proj_slice = \
data_obj.get_data_patterns()['PROJECTION']['slice_dims'][0]
image_key = np.zeros(data_obj.data.shape[proj_slice], dtype=int)
return image_key