Reorganise processors (#24)

* add test phase

* updated test

* removed unused import

* updated test

5 files changed, 186 insertions, 2 deletions

diff --git a/Wrappers/Python/ccpi/plugins/processors/AcquisitionDataPadder.py b/Wrappers/Python/ccpi/plugins/processors/AcquisitionDataPadder.py
new file mode 100755
index 0000000..4033c7b
--- /dev/null
+++ b/Wrappers/Python/ccpi/plugins/processors/AcquisitionDataPadder.py
@@ -0,0 +1,116 @@
+# -*- coding: utf-8 -*-

+"""

+Created on Tue Apr 30 13:43:52 2019

+

+@author: ofn77899

+"""

+from ccpi.framework import DataProcessor, DataContainer, AcquisitionData,\

+ AcquisitionGeometry, ImageGeometry, ImageData

+from ccpi.reconstruction.parallelbeam import alg as pbalg

+import numpy

+

+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, out=None):

+        projections = self.get_input()

+        w = projections.get_dimension_size('horizontal')

+        print ("horizontal ", w)

+        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 )

+        

+        print ("geom", geom)

+        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

diff --git a/Wrappers/Python/ccpi/plugins/processors/__init__.py b/Wrappers/Python/ccpi/plugins/processors/__init__.py
index e688671..da13b98 100644
--- a/Wrappers/Python/ccpi/plugins/processors/__init__.py
+++ b/Wrappers/Python/ccpi/plugins/processors/__init__.py
@@ -1,4 +1,4 @@
 from .processors import setupCCPiGeometries

 from .processors import CCPiForwardProjector

 from .processors import CCPiBackwardProjector

-from .processors import AcquisitionDataPadder

+from .AcquisitionDataPadder import AcquisitionDataPadder

diff --git a/Wrappers/Python/conda-recipe/meta.yaml b/Wrappers/Python/conda-recipe/meta.yaml
index ab67b0c..c9126d4 100644
--- a/Wrappers/Python/conda-recipe/meta.yaml
+++ b/Wrappers/Python/conda-recipe/meta.yaml
@@ -8,7 +8,20 @@ build:
   script_env:
     - CIL_VERSION   
 #  number: 0
-  
+test:
+  requires:
+    - python-wget
+    - cvxpy # [ unix and py36 and np115 ]
+
+  source_files:
+    - ./test # [win]
+    - ./ccpi/Wrappers/Python/test # [not win] 
+
+  commands:
+    - python -c "import os; print (os.getcwd())"
+    - python -m unittest discover # [win]
+    - python -m unittest discover -s ccpi/Wrappers/Python/test # [not win]
+    
 requirements:
   build:
     - python
diff --git a/Wrappers/Python/test/__init__.py b/Wrappers/Python/test/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/Wrappers/Python/test/__init__.py
diff --git a/Wrappers/Python/test/test_Processors.py b/Wrappers/Python/test/test_Processors.py
new file mode 100755
index 0000000..0c43126
--- /dev/null
+++ b/Wrappers/Python/test/test_Processors.py
@@ -0,0 +1,55 @@
+# -*- coding: utf-8 -*-

+"""

+Created on Tue Apr 30 14:39:20 2019

+

+@author: ofn77899

+"""

+

+import sys

+import unittest

+import numpy

+from ccpi.framework import DataProcessor

+from ccpi.framework import DataContainer

+from ccpi.framework import ImageData

+from ccpi.framework import AcquisitionData

+from ccpi.framework import ImageGeometry

+from ccpi.framework import AcquisitionGeometry

+from timeit import default_timer as timer

+from ccpi.io.reader import NexusReader

+from ccpi.processors import CenterOfRotationFinder

+from ccpi.plugins.processors import AcquisitionDataPadder

+import wget

+import os

+import math

+

+class TestDataProcessor(unittest.TestCase):

+    def setUp(self):

+        wget.download('https://github.com/DiamondLightSource/Savu/raw/master/test_data/data/24737_fd.nxs')

+        self.filename = '24737_fd.nxs'

+

+    def tearDown(self):

+        os.remove(self.filename)

+

+    def test_AcquisitionDataPadder(self):

+        reader = NexusReader(self.filename)

+        ad = reader.get_acquisition_data_whole()

+        print (ad.geometry)

+        cf = CenterOfRotationFinder()

+        cf.set_input(ad)

+        print ("Center of rotation", cf.get_output())

+        self.assertAlmostEqual(86.25, cf.get_output())

+        

+        adp = AcquisitionDataPadder(acquisition_geometry=cf.get_input().geometry,center_of_rotation=cf.get_output(),pad_value=0)

+        adp.set_input(ad)

+        padded_data = adp.get_output()

+        print ("Padded data shape", padded_data.shape)

+        print ("      " , padded_data.dimension_labels)

+        idx = None

+        for k,v in padded_data.dimension_labels.items():

+            if v == AcquisitionGeometry.HORIZONTAL:

+                idx = k

+

+        padded_axis = padded_data.shape[idx]

+        self.assertEqual(padded_axis , math.ceil(cf.get_output() * 2))

+        numpy.save("pippo.npy" , padded_data.as_array())

+