From 5d6cabba5428f9ddf4c4487ffc2668a6fb70cb17 Mon Sep 17 00:00:00 2001
From: Edoardo Pasca <edo.paskino@gmail.com>
Date: Tue, 15 May 2018 16:37:40 +0200
Subject: move padder to plugins (#121)

---
 Wrappers/Python/ccpi/processors.py     | 105 ---------------------------------
 Wrappers/Python/conda-recipe/meta.yaml |   1 -
 2 files changed, 106 deletions(-)

diff --git a/Wrappers/Python/ccpi/processors.py b/Wrappers/Python/ccpi/processors.py
index b65722e..a2d0446 100755
--- a/Wrappers/Python/ccpi/processors.py
+++ b/Wrappers/Python/ccpi/processors.py
@@ -19,7 +19,6 @@
 
 from ccpi.framework import DataProcessor, DataContainer, AcquisitionData,\
  AcquisitionGeometry, ImageGeometry, ImageData
-from ccpi.reconstruction.parallelbeam import alg as pbalg
 import numpy
 from scipy import ndimage
 
@@ -389,107 +388,3 @@ class CenterOfRotationFinder(DataProcessor):
         
         return cor
 
-            
-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/conda-recipe/meta.yaml b/Wrappers/Python/conda-recipe/meta.yaml
index c6b1940..f72c980 100644
--- a/Wrappers/Python/conda-recipe/meta.yaml
+++ b/Wrappers/Python/conda-recipe/meta.yaml
@@ -18,7 +18,6 @@ requirements:
   run:
     - python
     - numpy
-    #- ccpi-reconstruction
     - matplotlib
 	
 about:
-- 
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