renaming according to CCPPETMR conventions

Renamed VolumeData to ImageData
Renamed SinogramData to AcquisitionData
NOT renamed DataSetProcessor
methods are now lower_case not camelCase

Moved astra_processor to package astra
Updated the demos

6 files changed, 139 insertions, 140 deletions

diff --git a/Wrappers/Python/ccpi/astra/astra_processors.py b/Wrappers/Python/ccpi/astra/astra_processors.py
index f51aec9..bf6048b 100644
--- a/Wrappers/Python/ccpi/astra/astra_processors.py
+++ b/Wrappers/Python/ccpi/astra/astra_processors.py
@@ -1,17 +1,16 @@
-from ccpi.framework import DataSetProcessor, DataSet, VolumeData, SinogramData
+from ccpi.framework import DataSetProcessor, ImageData, AcquisitionData
 from ccpi.astra.astra_utils import convert_geometry_to_astra
 import astra
-import numpy
 
 
 class AstraForwardProjector(DataSetProcessor):
     '''AstraForwardProjector
     
-    Forward project VolumeDataSet to SinogramDataSet using ASTRA proj_id.
+    Forward project ImageData to AcquisitionData using ASTRA proj_id.
     
-    Input: VolumeDataSet
+    Input: ImageData
     Parameter: proj_id
-    Output: SinogramDataSet
+    Output: AcquisitionData
     '''
     
     def __init__(self,
@@ -50,7 +49,7 @@ class AstraForwardProjector(DataSetProcessor):
         else:
             NotImplemented
     
-    def checkInput(self, dataset):
+    def check_input(self, dataset):
         if dataset.number_of_dimensions == 3 or\
            dataset.number_of_dimensions == 2:
                return True
@@ -68,24 +67,24 @@ class AstraForwardProjector(DataSetProcessor):
         self.sinogram_geometry = sinogram_geometry
     
     def process(self):
-        IM = self.getInput()
-        DATA = SinogramData(geometry=self.sinogram_geometry)
+        IM = self.get_input()
+        DATA = AcquisitionData(geometry=self.sinogram_geometry)
         #sinogram_id, DATA = astra.create_sino( IM.as_array(), 
         #                           self.proj_id)
         sinogram_id, DATA.array = astra.create_sino(IM.as_array(), 
                                                            self.proj_id)
         astra.data2d.delete(sinogram_id)
-        #return SinogramData(array=DATA, geometry=self.sinogram_geometry)
+        #return AcquisitionData(array=DATA, geometry=self.sinogram_geometry)
         return DATA
 
 class AstraBackProjector(DataSetProcessor):
     '''AstraBackProjector
     
-    Back project SinogramDataSet to VolumeDataSet using ASTRA proj_id.
+    Back project AcquisitionData to ImageData using ASTRA proj_id.
     
-    Input: SinogramDataSet
+    Input: AcquisitionData
     Parameter: proj_id
-    Output: VolumeDataSet 
+    Output: ImageData
     '''
     
     def __init__(self,
@@ -124,7 +123,7 @@ class AstraBackProjector(DataSetProcessor):
         else:
             NotImplemented
     
-    def checkInput(self, dataset):
+    def check_input(self, dataset):
         if dataset.number_of_dimensions == 3 or dataset.number_of_dimensions == 2:
                return True
         else:
@@ -141,8 +140,8 @@ class AstraBackProjector(DataSetProcessor):
         self.sinogram_geometry = sinogram_geometry
     
     def process(self):
-        DATA = self.getInput()
-        IM = VolumeData(geometry=self.volume_geometry)
+        DATA = self.get_input()
+        IM = ImageData(geometry=self.volume_geometry)
         rec_id, IM.array = astra.create_backprojection(DATA.as_array(),
                             self.proj_id)
         astra.data2d.delete(rec_id)
@@ -151,13 +150,13 @@ class AstraBackProjector(DataSetProcessor):
 class AstraForwardProjectorMC(AstraForwardProjector):
     '''AstraForwardProjector Multi channel
     
-    Forward project VolumeDataSet to SinogramDataSet using ASTRA proj_id.
+    Forward project ImageData to AcquisitionDataSet using ASTRA proj_id.
     
-    Input: VolumeDataSet
+    Input: ImageDataSet
     Parameter: proj_id
-    Output: SinogramDataSet
+    Output: AcquisitionData
     '''
-    def checkInput(self, dataset):
+    def check_input(self, dataset):
         if dataset.number_of_dimensions == 2 or \
            dataset.number_of_dimensions == 3 or \
            dataset.number_of_dimensions == 4:
@@ -166,9 +165,9 @@ class AstraForwardProjectorMC(AstraForwardProjector):
             raise ValueError("Expected input dimensions is 2 or 3, got {0}"\
                              .format(dataset.number_of_dimensions))
     def process(self):
-        IM = self.getInput()
-        #create the output Sinogram
-        DATA = SinogramData(geometry=self.sinogram_geometry)
+        IM = self.get_input()
+        #create the output AcquisitionData
+        DATA = AcquisitionData(geometry=self.sinogram_geometry)
         
         for k in range(DATA.geometry.channels):
             sinogram_id, DATA.as_array()[k] = astra.create_sino(IM.as_array()[k], 
@@ -179,13 +178,13 @@ class AstraForwardProjectorMC(AstraForwardProjector):
 class AstraBackProjectorMC(AstraBackProjector):
     '''AstraBackProjector Multi channel
     
-    Back project SinogramDataSet to VolumeDataSet using ASTRA proj_id.
+    Back project AcquisitionData to ImageData using ASTRA proj_id.
     
-    Input: SinogramDataSet
+    Input: AcquisitionData
     Parameter: proj_id
-    Output: VolumeDataSet 
+    Output: ImageData
     '''
-    def checkInput(self, dataset):
+    def check_input(self, dataset):
         if dataset.number_of_dimensions == 2 or \
            dataset.number_of_dimensions == 3 or \
            dataset.number_of_dimensions == 4:
@@ -194,12 +193,13 @@ class AstraBackProjectorMC(AstraBackProjector):
             raise ValueError("Expected input dimensions is 2 or 3, got {0}"\
                              .format(dataset.number_of_dimensions))
     def process(self):
-        DATA = self.getInput()
+        DATA = self.get_input()
         
-        IM = VolumeData(geometry=self.volume_geometry)
+        IM = ImageData(geometry=self.volume_geometry)
         
         for k in range(IM.geometry.channels):
-            rec_id, IM.as_array()[k] = astra.create_backprojection(DATA.as_array()[k], 
-                                  self.proj_id)
+            rec_id, IM.as_array()[k] = astra.create_backprojection(
+                    DATA.as_array()[k], 
+                    self.proj_id)
             astra.data2d.delete(rec_id)
         return IM
\ No newline at end of file
diff --git a/Wrappers/Python/ccpi/framework.py b/Wrappers/Python/ccpi/framework.py
index b2f8a7e..3409611 100644
--- a/Wrappers/Python/ccpi/framework.py
+++ b/Wrappers/Python/ccpi/framework.py
@@ -94,7 +94,7 @@ class CCPiBaseClass(ABC):
         if self.debug:
             print ("{0}: {1}".format(self.__class__.__name__, msg))
             
-class DataSet(object):
+class DataContainer(object):
     '''Generic class to hold data
     
     Data is currently held in a numpy arrays'''
@@ -106,7 +106,7 @@ class DataSet(object):
         self.shape = numpy.shape(array)
         self.number_of_dimensions = len (self.shape)
         self.dimension_labels = {}
-        self.geometry = None # Only relevant for SinogramData and VolumeData
+        self.geometry = None # Only relevant for AcquisitionData and ImageData
         
         if dimension_labels is not None and \
            len (dimension_labels) == self.number_of_dimensions:
@@ -134,10 +134,10 @@ class DataSet(object):
         
 
     def as_array(self, dimensions=None):
-        '''Returns the DataSet as Numpy Array
+        '''Returns the DataContainer as Numpy Array
         
         Returns the pointer to the array if dimensions is not set.
-        If dimensions is set, it first creates a new DataSet with the subset
+        If dimensions is set, it first creates a new DataContainer with the subset
         and then it returns the pointer to the array'''
         if dimensions is not None:
             return self.subset(dimensions).as_array()
@@ -145,7 +145,7 @@ class DataSet(object):
     
     
     def subset(self, dimensions=None, **kw):
-        '''Creates a DataSet containing a subset of self according to the 
+        '''Creates a DataContainer containing a subset of self according to the 
         labels in dimensions'''
         if dimensions is None:
             return self.array.copy()
@@ -155,7 +155,7 @@ class DataSet(object):
             proceed = True
             unknown_key = ''
             # axis_order contains the order of the axis that the user wants
-            # in the output DataSet
+            # in the output DataContainer
             axis_order = []
             if type(dimensions) == list:
                 for dl in dimensions:
@@ -221,12 +221,12 @@ class DataSet(object):
                                      numpy.shape(array)))
         self.array = array[:]
         
-    def checkDimensions(self, other):
+    def check_dimensions(self, other):
         return self.shape == other.shape
         
     def __add__(self, other):
-        if issubclass(type(other), DataSet):    
-            if self.checkDimensions(other):
+        if issubclass(type(other), DataContainer):    
+            if self.check_dimensions(other):
                 out = self.as_array() + other.as_array()
                 return type(self)(out, 
                                deep_copy=True, 
@@ -242,13 +242,13 @@ class DataSet(object):
                                dimension_labels=self.dimension_labels,
                                geometry=self.geometry)
         else:
-            raise TypeError('Cannot {0} DataSet with {1}'.format("add" ,
+            raise TypeError('Cannot {0} DataContainer with {1}'.format("add" ,
                             type(other)))
     # __add__
     
     def __sub__(self, other):
-        if issubclass(type(other), DataSet):    
-            if self.checkDimensions(other):
+        if issubclass(type(other), DataContainer):    
+            if self.check_dimensions(other):
                 out = self.as_array() - other.as_array()
                 return type(self)(out, 
                                deep_copy=True, 
@@ -263,7 +263,7 @@ class DataSet(object):
                                dimension_labels=self.dimension_labels,
                                geometry=self.geometry)
         else:
-            raise TypeError('Cannot {0} DataSet with {1}'.format("subtract" ,
+            raise TypeError('Cannot {0} DataContainer with {1}'.format("subtract" ,
                             type(other)))
     # __sub__
     def __truediv__(self,other):
@@ -271,8 +271,8 @@ class DataSet(object):
     
     def __div__(self, other):
         print ("calling __div__")
-        if issubclass(type(other), DataSet):    
-            if self.checkDimensions(other):
+        if issubclass(type(other), DataContainer):    
+            if self.check_dimensions(other):
                 out = self.as_array() / other.as_array()
                 return type(self)(out, 
                                deep_copy=True, 
@@ -287,13 +287,13 @@ class DataSet(object):
                                dimension_labels=self.dimension_labels,
                                geometry=self.geometry)
         else:
-            raise TypeError('Cannot {0} DataSet with {1}'.format("divide" ,
+            raise TypeError('Cannot {0} DataContainer with {1}'.format("divide" ,
                             type(other)))
     # __div__
     
     def __pow__(self, other):
-        if issubclass(type(other), DataSet):    
-            if self.checkDimensions(other):
+        if issubclass(type(other), DataContainer):    
+            if self.check_dimensions(other):
                 out = self.as_array() ** other.as_array()
                 return type(self)(out, 
                                deep_copy=True, 
@@ -308,13 +308,13 @@ class DataSet(object):
                                dimension_labels=self.dimension_labels,
                                geometry=self.geometry)
         else:
-            raise TypeError('Cannot {0} DataSet with {1}'.format("power" ,
+            raise TypeError('Cannot {0} DataContainer with {1}'.format("power" ,
                             type(other)))
     # __pow__
     
     def __mul__(self, other):
-        if issubclass(type(other), DataSet):    
-            if self.checkDimensions(other):
+        if issubclass(type(other), DataContainer):    
+            if self.check_dimensions(other):
                 out = self.as_array() * other.as_array()
                 return type(self)(out, 
                                deep_copy=True, 
@@ -329,7 +329,7 @@ class DataSet(object):
                                dimension_labels=self.dimension_labels,
                                geometry=self.geometry)
         else:
-            raise TypeError('Cannot {0} DataSet with {1}'.format("multiply" ,
+            raise TypeError('Cannot {0} DataContainer with {1}'.format("multiply" ,
                             type(other)))
     # __mul__
     
@@ -386,8 +386,8 @@ class DataSet(object):
             return type(self)(fother ** self.array , 
                            dimension_labels=self.dimension_labels,
                            geometry=self.geometry)
-        elif issubclass(other, DataSet):
-            if self.checkDimensions(other):
+        elif issubclass(other, DataContainer):
+            if self.check_dimensions(other):
                 return type(self)(other.as_array() ** self.array , 
                            dimension_labels=self.dimension_labels,
                            geometry=self.geometry)
@@ -437,8 +437,8 @@ class DataSet(object):
                 
                     
                 
-class VolumeData(DataSet):
-    '''DataSet for holding 2D or 3D dataset'''
+class ImageData(DataContainer):
+    '''DataContainer for holding 2D or 3D DataContainer'''
     def __init__(self, 
                  array = None, 
                  deep_copy=True, 
@@ -476,24 +476,24 @@ class VolumeData(DataSet):
                                       'horizontal_x']
                         
                 array = numpy.zeros( shape , dtype=numpy.float32) 
-                super(VolumeData, self).__init__(array, deep_copy,
+                super(ImageData, self).__init__(array, deep_copy,
                                  dim_labels, **kwargs)
                 
             else:
-                raise ValueError('Please pass either a DataSet, ' +\
+                raise ValueError('Please pass either a DataContainer, ' +\
                                  'a numpy array or a geometry')
         else:
-            if type(array) == DataSet:
-                # if the array is a DataSet get the info from there
+            if type(array) == DataContainer:
+                # if the array is a DataContainer get the info from there
                 if not ( array.number_of_dimensions == 2 or \
                          array.number_of_dimensions == 3 or \
                          array.number_of_dimensions == 4):
                     raise ValueError('Number of dimensions are not 2 or 3 or 4: {0}'\
                                      .format(array.number_of_dimensions))
                 
-                #DataSet.__init__(self, array.as_array(), deep_copy,
+                #DataContainer.__init__(self, array.as_array(), deep_copy,
                 #                 array.dimension_labels, **kwargs)
-                super(VolumeData, self).__init__(array.as_array(), deep_copy,
+                super(ImageData, self).__init__(array.as_array(), deep_copy,
                                  array.dimension_labels, **kwargs)
             elif type(array) == numpy.ndarray:
                 if not ( array.ndim == 2 or array.ndim == 3 or array.ndim == 4 ):
@@ -512,8 +512,8 @@ class VolumeData(DataSet):
                         dimension_labels = ['horizontal_y' , 
                                       'horizontal_x']   
                 
-                #DataSet.__init__(self, array, deep_copy, dimension_labels, **kwargs)
-                super(VolumeData, self).__init__(array, deep_copy, 
+                #DataContainer.__init__(self, array, deep_copy, dimension_labels, **kwargs)
+                super(ImageData, self).__init__(array, deep_copy, 
                      dimension_labels, **kwargs)
        
         # load metadata from kwargs if present
@@ -526,8 +526,8 @@ class VolumeData(DataSet):
                         self.spacing = value
                         
 
-class SinogramData(DataSet):
-    '''DataSet for holding 2D or 3D sinogram'''
+class AcquisitionData(DataContainer):
+    '''DataContainer for holding 2D or 3D sinogram'''
     def __init__(self, 
                  array = None, 
                  deep_copy=True, 
@@ -565,21 +565,21 @@ class SinogramData(DataSet):
                                       'horizontal']
                 
                 array = numpy.zeros( shape , dtype=numpy.float32) 
-                super(SinogramData, self).__init__(array, deep_copy,
+                super(AcquisitionData, self).__init__(array, deep_copy,
                                  dim_labels, **kwargs)
         else:
             
-            if type(array) == DataSet:
-                # if the array is a DataSet get the info from there
+            if type(array) == DataContainer:
+                # if the array is a DataContainer get the info from there
                 if not ( array.number_of_dimensions == 2 or \
                          array.number_of_dimensions == 3 or \
                          array.number_of_dimensions == 4):
                     raise ValueError('Number of dimensions are not 2 or 3 or 4: {0}'\
                                      .format(array.number_of_dimensions))
                 
-                #DataSet.__init__(self, array.as_array(), deep_copy,
+                #DataContainer.__init__(self, array.as_array(), deep_copy,
                 #                 array.dimension_labels, **kwargs)
-                super(SinogramData, self).__init__(array.as_array(), deep_copy,
+                super(AcquisitionData, self).__init__(array.as_array(), deep_copy,
                                  array.dimension_labels, **kwargs)
             elif type(array) == numpy.ndarray:
                 if not ( array.ndim == 2 or array.ndim == 3 or array.ndim == 4 ):
@@ -598,16 +598,16 @@ class SinogramData(DataSet):
                         dimension_labels = ['angle' , 
                                       'horizontal']   
                 
-                #DataSet.__init__(self, array, deep_copy, dimension_labels, **kwargs)
-                super(SinogramData, self).__init__(array, deep_copy, 
+                #DataContainer.__init__(self, array, deep_copy, dimension_labels, **kwargs)
+                super(AcquisitionData, self).__init__(array, deep_copy, 
                      dimension_labels, **kwargs)
                 
             
 class DataSetProcessor(object):
-    '''Defines a generic DataSet processor
+    '''Defines a generic DataContainer processor
     
-    accepts DataSet as inputs and 
-    outputs DataSet
+    accepts DataContainer as inputs and 
+    outputs DataContainer
     additional attributes can be defined with __setattr__
     '''
     
@@ -624,7 +624,7 @@ class DataSetProcessor(object):
     
     def __setattr__(self, name, value):
         if name == 'input':
-            self.setInput(value)
+            self.set_input(value)
         elif name in self.__dict__.keys():
             self.__dict__[name] = value
             self.__dict__['mTime'] = datetime.now()
@@ -632,23 +632,23 @@ class DataSetProcessor(object):
             raise KeyError('Attribute {0} not found'.format(name))
         #pass
     
-    def setInput(self, dataset):
-        if issubclass(type(dataset), DataSet):
-            if self.checkInput(dataset):
+    def set_input(self, dataset):
+        if issubclass(type(dataset), DataContainer):
+            if self.check_input(dataset):
                 self.__dict__['input'] = dataset
         else:
             raise TypeError("Input type mismatch: got {0} expecting {1}"\
-                            .format(type(dataset), DataSet))
+                            .format(type(dataset), DataContainer))
     
-    def checkInput(self, dataset):
-        '''Checks parameters of the input DataSet
+    def check_input(self, dataset):
+        '''Checks parameters of the input DataContainer
         
-        Should raise an Error if the DataSet does not match expectation, e.g.
-        if the expected input DataSet is 3D and the Processor expects 2D.
+        Should raise an Error if the DataContainer does not match expectation, e.g.
+        if the expected input DataContainer is 3D and the Processor expects 2D.
         '''
-        raise NotImplementedError('Implement basic checks for input DataSet')
+        raise NotImplementedError('Implement basic checks for input DataContainer')
         
-    def getOutput(self):
+    def get_output(self):
         if None in self.__dict__.values():
             raise ValueError('Not all parameters have been passed')
         shouldRun = False
@@ -665,21 +665,21 @@ class DataSetProcessor(object):
         self.runTime = datetime.now()
         return self.process()
     
-    def setInputProcessor(self, processor):
+    def set_input_processor(self, processor):
         if issubclass(type(processor), DataSetProcessor):
             self.__dict__['input'] = processor
         else:
             raise TypeError("Input type mismatch: got {0} expecting {1}"\
                             .format(type(processor), DataSetProcessor))
         
-    def getInput(self):
-        '''returns the input DataSet
+    def get_input(self):
+        '''returns the input DataContainer
         
         It is useful in the case the user has provided a DataSetProcessor as
         input
         '''
         if issubclass(type(self.input), DataSetProcessor):
-            dsi = self.input.getOutput()
+            dsi = self.input.get_output()
         else:
             dsi = self.input
         return dsi
@@ -691,8 +691,8 @@ class DataSetProcessor23D(DataSetProcessor):
     '''Regularizers DataSetProcessor
     '''
             
-    def checkInput(self, dataset):
-        '''Checks number of dimensions input DataSet
+    def check_input(self, dataset):
+        '''Checks number of dimensions input DataContainer
         
         Expected input is 2D or 3D
         '''
@@ -714,7 +714,7 @@ class AX(DataSetProcessor):
 
     a is a scalar
 
-    x a DataSet.
+    x a DataContainer.
     '''
     
     def __init__(self):
@@ -725,15 +725,15 @@ class AX(DataSetProcessor):
         #DataSetProcessor.__init__(self, **kwargs)
         super(AX, self).__init__(**kwargs)
     
-    def checkInput(self, dataset):
+    def check_input(self, dataset):
         return True
         
     def process(self):
         
-        dsi = self.getInput()
+        dsi = self.get_input()
         a = self.scalar
         
-        y = DataSet( a * dsi.as_array() , True, 
+        y = DataContainer( a * dsi.as_array() , True, 
                     dimension_labels=dsi.dimension_labels )
         #self.setParameter(output_dataset=y)
         return y
@@ -744,7 +744,7 @@ class AX(DataSetProcessor):
 class PixelByPixelDataSetProcessor(DataSetProcessor):
     '''Example DataSetProcessor
     
-    This processor applies a python function to each pixel of the DataSet
+    This processor applies a python function to each pixel of the DataContainer
     
     f is a python function
 
@@ -758,18 +758,18 @@ class PixelByPixelDataSetProcessor(DataSetProcessor):
         #DataSetProcessor.__init__(self, **kwargs)
         super(PixelByPixelDataSetProcessor, self).__init__(**kwargs)
         
-    def checkInput(self, dataset):
+    def check_input(self, dataset):
         return True
     
     def process(self):
         
         pyfunc = self.pyfunc
-        dsi = self.getInput()
+        dsi = self.get_input()
         
         eval_func = numpy.frompyfunc(pyfunc,1,1)
 
         
-        y = DataSet( eval_func( dsi.as_array() ) , True, 
+        y = DataContainer( eval_func( dsi.as_array() ) , True, 
                     dimension_labels=dsi.dimension_labels )
         return y
     
@@ -786,7 +786,7 @@ if __name__ == '__main__':
     print("a refcount " , sys.getrefcount(a))
     a = numpy.reshape(a, shape)
     print("a refcount " , sys.getrefcount(a))
-    ds = DataSet(a, False, ['X', 'Y','Z' ,'W'])
+    ds = DataContainer(a, False, ['X', 'Y','Z' ,'W'])
     print("a refcount " , sys.getrefcount(a))
     print ("ds label {0}".format(ds.dimension_labels))
     subset = ['W' ,'X']
@@ -797,34 +797,34 @@ if __name__ == '__main__':
     c = ds.subset(['Z','W','X'])
     print("a refcount " , sys.getrefcount(a))
     
-    # Create a VolumeData sharing the array with c
-    volume0 = VolumeData(c.as_array(), False, dimensions = c.dimension_labels)
-    volume1 = VolumeData(c, False)
+    # Create a ImageData sharing the array with c
+    volume0 = ImageData(c.as_array(), False, dimensions = c.dimension_labels)
+    volume1 = ImageData(c, False)
     
     print ("volume0 {0} volume1 {1}".format(id(volume0.array),
            id(volume1.array)))
     
-    # Create a VolumeData copying the array from c
-    volume2 = VolumeData(c.as_array(), dimensions = c.dimension_labels)
-    volume3 = VolumeData(c)
+    # Create a ImageData copying the array from c
+    volume2 = ImageData(c.as_array(), dimensions = c.dimension_labels)
+    volume3 = ImageData(c)
     
     print ("volume2 {0} volume3 {1}".format(id(volume2.array),
            id(volume3.array)))
         
     # single number DataSet
-    sn = DataSet(numpy.asarray([1]))
+    sn = DataContainer(numpy.asarray([1]))
     
     ax = AX()
     ax.scalar = 2
-    ax.setInput(c)
+    ax.set_input(c)
     #ax.apply()
     print ("ax  in {0} out {1}".format(c.as_array().flatten(),
-           ax.getOutput().as_array().flatten()))
+           ax.get_output().as_array().flatten()))
     axm = AX()
     axm.scalar = 0.5
-    axm.setInput(c)
+    axm.set_input(c)
     #axm.apply()
-    print ("axm in {0} out {1}".format(c.as_array(), axm.getOutput().as_array()))
+    print ("axm in {0} out {1}".format(c.as_array(), axm.get_output().as_array()))
     
     # create a PixelByPixelDataSetProcessor
     
@@ -832,20 +832,20 @@ if __name__ == '__main__':
     pyfunc = lambda x: -x if x > 20 else x
     clip = PixelByPixelDataSetProcessor()
     clip.pyfunc = pyfunc 
-    clip.setInput(c)    
+    clip.set_input(c)    
     #clip.apply()
     
-    print ("clip in {0} out {1}".format(c.as_array(), clip.getOutput().as_array()))
+    print ("clip in {0} out {1}".format(c.as_array(), clip.get_output().as_array()))
     
     #dsp = DataSetProcessor()
-    #dsp.setInput(ds)
+    #dsp.set_input(ds)
     #dsp.input = a
     # pipeline
 
     chain = AX()
     chain.scalar = 0.5
-    chain.setInputProcessor(ax)
-    print ("chain in {0} out {1}".format(ax.getOutput().as_array(), chain.getOutput().as_array()))
+    chain.set_input_processor(ax)
+    print ("chain in {0} out {1}".format(ax.get_output().as_array(), chain.get_output().as_array()))
     
     # testing arithmetic operations
     
@@ -875,14 +875,14 @@ if __name__ == '__main__':
     
     s = [i for i in range(3 * 4 * 4)]
     s = numpy.reshape(numpy.asarray(s), (3,4,4))
-    sino = SinogramData( s )
+    sino = AcquisitionData( s )
     
     shape = (4,3,2)
     a = [i for i in range(2*3*4)]
     a = numpy.asarray(a)
     a = numpy.reshape(a, shape)
     print (numpy.shape(a))
-    ds = DataSet(a, True, ['X', 'Y','Z'])
+    ds = DataContainer(a, True, ['X', 'Y','Z'])
     # this means that I expect the X to be of length 2 ,
     # y of length 3 and z of length 4
     subset = ['Y' ,'Z']
@@ -896,13 +896,13 @@ if __name__ == '__main__':
     print ("shape b 2,3? {0}".format(numpy.shape(b1.as_array())))
     
     
-    # create VolumeData from geometry
+    # create ImageData from geometry
     vgeometry = geoms.VolumeGeometry(voxel_num_x=2, voxel_num_y=3, channels=2)
-    vol = VolumeData(geometry=vgeometry)
+    vol = ImageData(geometry=vgeometry)
     
     sgeometry = geoms.SinogramGeometry(dimension=2, angles=numpy.linspace(0, 180, num=20), 
                                        geom_type='parallel', pixel_num_v=3,
                                        pixel_num_h=5 , channels=2)
-    sino = SinogramData(geometry=sgeometry)
+    sino = AcquisitionData(geometry=sgeometry)
     sino2 = sino.clone()
     
\ No newline at end of file
diff --git a/Wrappers/Python/ccpi/reconstruction/algs.py b/Wrappers/Python/ccpi/reconstruction/algs.py
index 088b36e..ec52fee 100644
--- a/Wrappers/Python/ccpi/reconstruction/algs.py
+++ b/Wrappers/Python/ccpi/reconstruction/algs.py
@@ -21,7 +21,6 @@ import numpy
 import time
 
 from ccpi.reconstruction.funcs import BaseFunction
-from ccpi.framework import SinogramData, VolumeData
 
 def FISTA(x_init, f=None, g=None, opt=None):
 
diff --git a/Wrappers/Python/ccpi/reconstruction/ops.py b/Wrappers/Python/ccpi/reconstruction/ops.py
index c21ff06..d6f31eb 100644
--- a/Wrappers/Python/ccpi/reconstruction/ops.py
+++ b/Wrappers/Python/ccpi/reconstruction/ops.py
@@ -19,10 +19,10 @@
 
 import numpy
 from scipy.sparse.linalg import svds
-from ccpi.framework import DataSet, VolumeData, SinogramData, DataSetProcessor
+from ccpi.framework import DataContainer
 
 # Maybe operators need to know what types they take as inputs/outputs
-# to not just use generic DataSet
+# to not just use generic DataContainer
 
 
 class Operator(object):
@@ -60,10 +60,10 @@ class LinearOperatorMatrix(Operator):
         super(LinearOperatorMatrix, self).__init__()
         
     def direct(self,x):
-        return DataSet(numpy.dot(self.A,x.as_array()))
+        return DataContainer(numpy.dot(self.A,x.as_array()))
     
     def adjoint(self,x):
-        return DataSet(numpy.dot(self.A.transpose(),x.as_array()))
+        return DataContainer(numpy.dot(self.A.transpose(),x.as_array()))
     
     def size(self):
         return self.A.shape
@@ -130,7 +130,7 @@ class FiniteDiff2D(Operator):
 def PowerMethodNonsquare(op,numiters):
     # Initialise random
     inputsize = op.size()[1]
-    x0 = DataSet(numpy.random.randn(inputsize[0],inputsize[1]))
+    x0 = DataContainer(numpy.random.randn(inputsize[0],inputsize[1]))
     s = numpy.zeros(numiters)
     # Loop
     for it in numpy.arange(numiters):
diff --git a/Wrappers/Python/wip/simple_demo.py b/Wrappers/Python/wip/simple_demo.py
index 766e448..99109a6 100644
--- a/Wrappers/Python/wip/simple_demo.py
+++ b/Wrappers/Python/wip/simple_demo.py
@@ -1,10 +1,10 @@
 #import sys
 #sys.path.append("..")
 
-from ccpi.framework import VolumeData
-from ccpi.reconstruction.algs import *
+from ccpi.framework import ImageData
+from ccpi.reconstruction.algs import FISTA, FBPD, CGLS
 from ccpi.reconstruction.funcs import Norm2sq, Norm1
-from ccpi.reconstruction.astra_ops import AstraProjectorSimple
+from ccpi.astra.astra_ops import AstraProjectorSimple
 from ccpi.reconstruction.geoms import VolumeGeometry, SinogramGeometry
 
 import numpy as np
@@ -16,7 +16,7 @@ test_case = 1   # 1=parallel2D, 2=cone2D
 N = 128
 
 vg = VolumeGeometry(voxel_num_x=N,voxel_num_y=N)
-Phantom = VolumeData(geometry=vg)
+Phantom = ImageData(geometry=vg)
 
 x = Phantom.as_array()
 x[round(N/4):round(3*N/4),round(N/4):round(3*N/4)] = 1.0
@@ -77,7 +77,7 @@ plt.show()
 f = Norm2sq(Aop,b,c=0.5)
 
 # Initial guess
-x_init = VolumeData(np.zeros(x.shape),geometry=vg)
+x_init = ImageData(np.zeros(x.shape),geometry=vg)
 
 # Run FISTA for least squares without regularization
 x_fista0, it0, timing0, criter0 = FISTA(x_init, f, None)
@@ -131,7 +131,7 @@ current = 1
 fig = plt.figure()
 # projections row
 a=fig.add_subplot(rows,cols,current)
-a.set_title('phantom {0}'.format(numpy.shape(Phantom.as_array())))
+a.set_title('phantom {0}'.format(np.shape(Phantom.as_array())))
 imgplot = plt.imshow(Phantom.as_array())
 
 current = current + 1
diff --git a/Wrappers/Python/wip/simple_mc_demo.py b/Wrappers/Python/wip/simple_mc_demo.py
index 0d976d7..0bd48dd 100755
--- a/Wrappers/Python/wip/simple_mc_demo.py
+++ b/Wrappers/Python/wip/simple_mc_demo.py
@@ -1,10 +1,10 @@
 #import sys
 #sys.path.append("..")
 
-from ccpi.framework import VolumeData, SinogramData
+from ccpi.framework import ImageData, AcquisitionData
 from ccpi.reconstruction.algs import FISTA
 from ccpi.reconstruction.funcs import Norm2sq, Norm1
-from ccpi.reconstruction.astra_ops import AstraProjectorMC
+from ccpi.astra.astra_ops import AstraProjectorMC
 from ccpi.reconstruction.geoms import VolumeGeometry, SinogramGeometry
 
 import numpy
@@ -18,7 +18,7 @@ M = 100
 numchannels = 3
 
 vg = VolumeGeometry(voxel_num_x=N,voxel_num_y=N,channels=numchannels)
-Phantom = VolumeData(geometry=vg)
+Phantom = ImageData(geometry=vg)
 
 x = Phantom.as_array()
 x[0 , round(N/4):round(3*N/4) , round(N/4):round(3*N/4)  ] = 1.0
@@ -49,7 +49,7 @@ plt.show()
 #vg = VolumeGeometry(N,N,None, 1,1,None,channels=numchannels)
 
 
-#Phantom = VolumeData(x,geometry=vg)
+#Phantom = ImageData(x,geometry=vg)
 
 # Set up measurement geometry
 angles_num = 20; # angles number
@@ -107,7 +107,7 @@ plt.show()
 f = Norm2sq(Aop,b,c=0.5)
 
 # Initial guess
-x_init = VolumeData(numpy.zeros(x.shape),geometry=vg)
+x_init = ImageData(numpy.zeros(x.shape),geometry=vg)
 
 # FISTA options
 opt = {'tol': 1e-4, 'iter': 200}