text: # Copyright 2019 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:: morph_proc
     :platform: Unix
     :synopsis: Wrapper around skimage morphology routines for 2D morphological processing of binary datasets
  
  .. moduleauthor:: Daniil Kazantsev <scientificsoftware@diamond.ac.uk>
  """
  
  from savu.plugins.plugin import Plugin
  from savu.plugins.driver.cpu_plugin import CpuPlugin
  from savu.plugins.utils import register_plugin
  
  import numpy as np
  # importing skimage functions
  from skimage.morphology import *
  
  @register_plugin
  class MorphProc(Plugin, CpuPlugin):
  
      def __init__(self):
          super(MorphProc, self).__init__("MorphProc")
  
      def setup(self):
  
          in_dataset, out_dataset = self.get_datasets()
          in_pData, out_pData = self.get_plugin_datasets()
          in_pData[0].plugin_data_setup(self.parameters['pattern'], 'single')
  
          out_dataset[0].create_dataset(in_dataset[0], dtype=np.uint8)
          out_pData[0].plugin_data_setup(self.parameters['pattern'], 'single')
  
      def pre_process(self):
          # extract given parameters
          self.disk_radius = self.parameters['disk_radius']
          self.morph_operation = self.parameters['morph_operation']
          self.selem = disk(self.disk_radius)
  
      def process_frames(self, data):
          # run morphological operations here:
          integerMax = np.max(data[0])
          if (np.sum(data[0]) > 0):
              morph_result = eval(self.morph_operation)(data[0], self.selem)
              morph_result = np.uint8(morph_result*integerMax)
          else:
              morph_result = np.uint8(np.zeros(np.shape(data[0])))
          return [morph_result]
  
      def nInput_datasets(self):
          return 1
      def nOutput_datasets(self):
          return 1
  