From 4f7b325602e113db8e8ecb4431675b78e4e578dc Mon Sep 17 00:00:00 2001
From: Edoardo Pasca <edo.paskino@gmail.com>
Date: Tue, 15 May 2018 16:37:34 +0200
Subject: moved padder to plugins (#14)

---
 Wrappers/Python/ccpi/plugins/processors.py | 103 +++++++++++++++++++++++++++++
 Wrappers/Python/wip/demo_nexus.py          |   3 +-
 2 files changed, 105 insertions(+), 1 deletion(-)

diff --git a/Wrappers/Python/ccpi/plugins/processors.py b/Wrappers/Python/ccpi/plugins/processors.py
index 9938b9e..d31c03b 100755
--- a/Wrappers/Python/ccpi/plugins/processors.py
+++ b/Wrappers/Python/ccpi/plugins/processors.py
@@ -198,3 +198,106 @@ class CCPiBackwardProjector(DataProcessor):
         else:
             raise ValueError('Cannot process cone beam')
             
+class AcquisitionDataPadder(DataProcessor):
+    '''Normalization based on flat and dark
+    
+    This processor read in a AcquisitionData and normalises it based on 
+    the instrument reading with and without incident photons or neutrons.
+    
+    Input: AcquisitionData
+    Parameter: 2D projection with flat field (or stack)
+               2D projection with dark field (or stack)
+    Output: AcquisitionDataSetn
+    '''
+    
+    def __init__(self, 
+                 center_of_rotation   = None,
+                 acquisition_geometry = None,
+                 pad_value            = 1e-5):
+        kwargs = {
+                  'acquisition_geometry' : acquisition_geometry, 
+                  'center_of_rotation'   : center_of_rotation,
+                  'pad_value'            : pad_value
+                  }
+        
+        super(AcquisitionDataPadder, self).__init__(**kwargs)
+        
+    def check_input(self, dataset):
+        if self.acquisition_geometry is None:
+            self.acquisition_geometry = dataset.geometry
+        if dataset.number_of_dimensions == 3:
+               return True
+        else:
+            raise ValueError("Expected input dimensions is 2 or 3, got {0}"\
+                             .format(dataset.number_of_dimensions))
+
+    def process(self):
+        projections = self.get_input()
+        w = projections.get_dimension_size('horizontal')
+        delta = w - 2 * self.center_of_rotation
+               
+        padded_width = int (
+                numpy.ceil(abs(delta)) + w
+                )
+        delta_pix = padded_width - w
+        
+        voxel_per_pixel = 1
+        geom = pbalg.pb_setup_geometry_from_acquisition(projections.as_array(),
+                                            self.acquisition_geometry.angles,
+                                            self.center_of_rotation,
+                                            voxel_per_pixel )
+        
+        padded_geometry = self.acquisition_geometry.clone()
+        
+        padded_geometry.pixel_num_h = geom['n_h']
+        padded_geometry.pixel_num_v = geom['n_v']
+        
+        delta_pix_h = padded_geometry.pixel_num_h - self.acquisition_geometry.pixel_num_h
+        delta_pix_v = padded_geometry.pixel_num_v - self.acquisition_geometry.pixel_num_v
+        
+        if delta_pix_h == 0:
+            delta_pix_h = delta_pix
+            padded_geometry.pixel_num_h = padded_width
+        #initialize a new AcquisitionData with values close to 0
+        out = AcquisitionData(geometry=padded_geometry)
+        out = out + self.pad_value
+        
+        
+        #pad in the horizontal-vertical plane -> slice on angles
+        if delta > 0:
+            #pad left of middle
+            command = "out.array["
+            for i in range(out.number_of_dimensions):
+                if out.dimension_labels[i] == 'horizontal':
+                    value = '{0}:{1}'.format(delta_pix_h, delta_pix_h+w)
+                    command = command + str(value)
+                else:
+                    if out.dimension_labels[i] == 'vertical' :
+                        value = '{0}:'.format(delta_pix_v)
+                        command = command + str(value)
+                    else:
+                        command = command + ":"
+                if i < out.number_of_dimensions -1:
+                    command = command + ','
+            command = command + '] = projections.array'
+            #print (command)    
+        else:
+            #pad right of middle
+            command = "out.array["
+            for i in range(out.number_of_dimensions):
+                if out.dimension_labels[i] == 'horizontal':
+                    value = '{0}:{1}'.format(0, w)
+                    command = command + str(value)
+                else:
+                    if out.dimension_labels[i] == 'vertical' :
+                        value = '{0}:'.format(delta_pix_v)
+                        command = command + str(value)
+                    else:
+                        command = command + ":"
+                if i < out.number_of_dimensions -1:
+                    command = command + ','
+            command = command + '] = projections.array'
+            #print (command)    
+            #cleaned = eval(command)
+        exec(command)
+        return out
\ No newline at end of file
diff --git a/Wrappers/Python/wip/demo_nexus.py b/Wrappers/Python/wip/demo_nexus.py
index 03739b1..ec30fd5 100755
--- a/Wrappers/Python/wip/demo_nexus.py
+++ b/Wrappers/Python/wip/demo_nexus.py
@@ -12,7 +12,8 @@ from ccpi.framework import ImageData, AcquisitionData, ImageGeometry, Acquisitio
 from ccpi.optimisation.algs import FISTA, FBPD, CGLS
 from ccpi.optimisation.funcs import Norm2sq, Norm1
 from ccpi.plugins.ops import CCPiProjectorSimple
-from ccpi.processors import Normalizer, CenterOfRotationFinder, AcquisitionDataPadder
+from ccpi.processors import Normalizer, CenterOfRotationFinder 
+from ccpi.plugins.processors import AcquisitionDataPadder
 from ccpi.io.reader import NexusReader
 
 # All external imports
-- 
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